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0704.1394

Tarik Had\v{z}i\'c

Tarik Hadzic, Rune Moller Jensen, Henrik Reif Andersen

Calculating Valid Domains for BDD-Based Interactive Configuration

cs.AI

In these notes we formally describe the functionality of Calculating Valid Domains from the BDD representing the solution space of valid configurations. The formalization is largely based on the CLab configuration framework.

0704.2010

Juliana Bernardes

Juliana S Bernardes, Alberto Davila, Vitor Santos Costa, Gerson Zaverucha

A study of structural properties on profiles HMMs

6 pages, 7 figures

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Motivation: Profile hidden Markov Models (pHMMs) are a popular and very useful tool in the detection of the remote homologue protein families. Unfortunately, their performance is not always satisfactory when proteins are in the 'twilight zone'. We present HMMER-STRUCT, a model construction algorithm and tool that tries to improve pHMM performance by using structural information while training pHMMs. As a first step, HMMER-STRUCT constructs a set of pHMMs. Each pHMM is constructed by weighting each residue in an aligned protein according to a specific structural property of the residue. Properties used were primary, secondary and tertiary structures, accessibility and packing. HMMER-STRUCT then prioritizes the results by voting. Results: We used the SCOP database to perform our experiments. Throughout, we apply leave-one-family-out cross-validation over protein superfamilies. First, we used the MAMMOTH-mult structural aligner to align the training set proteins. Then, we performed two sets of experiments. In a first experiment, we compared structure weighted models against standard pHMMs and against each other. In a second experiment, we compared the voting model against individual pHMMs. We compare method performance through ROC curves and through Precision/Recall curves, and assess significance through the paired two tailed t-test. Our results show significant performance improvements of all structurally weighted models over default HMMER, and a significant improvement in sensitivity of the combined models over both the original model and the structurally weighted models.

0704.3433

Tshilidzi Marwala

Tshilidzi Marwala and Bodie Crossingham

Bayesian approach to rough set

20 pages, 3 figures

cs.AI

This paper proposes an approach to training rough set models using Bayesian framework trained using Markov Chain Monte Carlo (MCMC) method. The prior probabilities are constructed from the prior knowledge that good rough set models have fewer rules. Markov Chain Monte Carlo sampling is conducted through sampling in the rough set granule space and Metropolis algorithm is used as an acceptance criteria. The proposed method is tested to estimate the risk of HIV given demographic data. The results obtained shows that the proposed approach is able to achieve an average accuracy of 58% with the accuracy varying up to 66%. In addition the Bayesian rough set give the probabilities of the estimated HIV status as well as the linguistic rules describing how the demographic parameters drive the risk of HIV.

0704.3515

Jegor Uglov Mr

J. Uglov, V. Schetinin, C. Maple

Comparing Robustness of Pairwise and Multiclass Neural-Network Systems for Face Recognition

10.1155/2008/468693

cs.AI

Noise, corruptions and variations in face images can seriously hurt the performance of face recognition systems. To make such systems robust, multiclass neuralnetwork classifiers capable of learning from noisy data have been suggested. However on large face data sets such systems cannot provide the robustness at a high level. In this paper we explore a pairwise neural-network system as an alternative approach to improving the robustness of face recognition. In our experiments this approach is shown to outperform the multiclass neural-network system in terms of the predictive accuracy on the face images corrupted by noise.

0704.3905

Marc Schoenauer

Christian Gagn\'e (INFORMATIQUE WGZ INC.), Mich\`ele Sebag (INRIA Futurs), Marc Schoenauer (INRIA Futurs), Marco Tomassini (ISI)

Ensemble Learning for Free with Evolutionary Algorithms ?

Dans GECCO (2007)

cs.AI

Evolutionary Learning proceeds by evolving a population of classifiers, from which it generally returns (with some notable exceptions) the single best-of-run classifier as final result. In the meanwhile, Ensemble Learning, one of the most efficient approaches in supervised Machine Learning for the last decade, proceeds by building a population of diverse classifiers. Ensemble Learning with Evolutionary Computation thus receives increasing attention. The Evolutionary Ensemble Learning (EEL) approach presented in this paper features two contributions. First, a new fitness function, inspired by co-evolution and enforcing the classifier diversity, is presented. Further, a new selection criterion based on the classification margin is proposed. This criterion is used to extract the classifier ensemble from the final population only (Off-line) or incrementally along evolution (On-line). Experiments on a set of benchmark problems show that Off-line outperforms single-hypothesis evolutionary learning and state-of-art Boosting and generates smaller classifier ensembles.

0705.0197

Tshilidzi Marwala

Tshilidzi Marwala, Unathi Mahola and Snehashish Chakraverty

Fault Classification in Cylinders Using Multilayer Perceptrons, Support Vector Machines and Guassian Mixture Models

10 pages, 2 figures, 4 tables

Computer Assisted Mechanics and Engineering Sciences, Vol. 14, No. 2, 2007.

cs.AI

Gaussian mixture models (GMM) and support vector machines (SVM) are introduced to classify faults in a population of cylindrical shells. The proposed procedures are tested on a population of 20 cylindrical shells and their performance is compared to the procedure, which uses multi-layer perceptrons (MLP). The modal properties extracted from vibration data are used to train the GMM, SVM and MLP. It is observed that the GMM produces 98%, SVM produces 94% classification accuracy while the MLP produces 88% classification rates.

0705.0693

Tshilidzi Marwala

Evan Hurwitz and Tshilidzi Marwala

Learning to Bluff

6 pages

cs.AI

The act of bluffing confounds game designers to this day. The very nature of bluffing is even open for debate, adding further complication to the process of creating intelligent virtual players that can bluff, and hence play, realistically. Through the use of intelligent, learning agents, and carefully designed agent outlooks, an agent can in fact learn to predict its opponents reactions based not only on its own cards, but on the actions of those around it. With this wider scope of understanding, an agent can in learn to bluff its opponents, with the action representing not an illogical action, as bluffing is often viewed, but rather as an act of maximising returns through an effective statistical optimisation. By using a tee dee lambda learning algorithm to continuously adapt neural network agent intelligence, agents have been shown to be able to learn to bluff without outside prompting, and even to learn to call each others bluffs in free, competitive play.

0705.0734

Sanjiang Li

Sanjiang Li and Mingsheng Ying

Soft constraint abstraction based on semiring homomorphism

18 pages, 1 figure

Theoretical Computer Science 403(2-3) 192-201, 2008

10.1016/j.tcs.2008.03.029

cs.AI

The semiring-based constraint satisfaction problems (semiring CSPs), proposed by Bistarelli, Montanari and Rossi \cite{BMR97}, is a very general framework of soft constraints. In this paper we propose an abstraction scheme for soft constraints that uses semiring homomorphism. To find optimal solutions of the concrete problem, the idea is, first working in the abstract problem and finding its optimal solutions, then using them to solve the concrete problem. In particular, we show that a mapping preserves optimal solutions if and only if it is an order-reflecting semiring homomorphism. Moreover, for a semiring homomorphism $\alpha$ and a problem $P$ over $S$, if $t$ is optimal in $\alpha(P)$, then there is an optimal solution $\bar{t}$ of $P$ such that $\bar{t}$ has the same value as $t$ in $\alpha(P)$.

0705.0761

Tshilidzi Marwala

Tshilidzi Marwala and Bodie Crossingham

Bayesian Approach to Neuro-Rough Models

24 pages, 5 figures, 1 table

cs.AI

This paper proposes a neuro-rough model based on multi-layered perceptron and rough set. The neuro-rough model is then tested on modelling the risk of HIV from demographic data. The model is formulated using Bayesian framework and trained using Monte Carlo method and Metropolis criterion. When the model was tested to estimate the risk of HIV infection given the demographic data it was found to give the accuracy of 62%. The proposed model is able to combine the accuracy of the Bayesian MLP model and the transparency of Bayesian rough set model.

0705.0969

Tshilidzi Marwala

Ishmael S. Msiza, Fulufhelo V. Nelwamondo and Tshilidzi Marwala

Artificial Neural Networks and Support Vector Machines for Water Demand Time Series Forecasting

6 pages

cs.AI

Water plays a pivotal role in many physical processes, and most importantly in sustaining human life, animal life and plant life. Water supply entities therefore have the responsibility to supply clean and safe water at the rate required by the consumer. It is therefore necessary to implement mechanisms and systems that can be employed to predict both short-term and long-term water demands. The increasingly growing field of computational intelligence techniques has been proposed as an efficient tool in the modelling of dynamic phenomena. The primary objective of this paper is to compare the efficiency of two computational intelligence techniques in water demand forecasting. The techniques under comparison are the Artificial Neural Networks (ANNs) and the Support Vector Machines (SVMs). In this study it was observed that the ANNs perform better than the SVMs. This performance is measured against the generalisation ability of the two.

0705.1031

Tshilidzi Marwala

F.V. Nelwamondo and T. Marwala

Fuzzy Artmap and Neural Network Approach to Online Processing of Inputs with Missing Values

7 pages

cs.AI

An ensemble based approach for dealing with missing data, without predicting or imputing the missing values is proposed. This technique is suitable for online operations of neural networks and as a result, is used for online condition monitoring. The proposed technique is tested in both classification and regression problems. An ensemble of Fuzzy-ARTMAPs is used for classification whereas an ensemble of multi-layer perceptrons is used for the regression problem. Results obtained using this ensemble-based technique are compared to those obtained using a combination of auto-associative neural networks and genetic algorithms and findings show that this method can perform up to 9% better in regression problems. Another advantage of the proposed technique is that it eliminates the need for finding the best estimate of the data, and hence, saves time.

0705.1209

Tshilidzi Marwala

E. Habtemariam, T. Marwala and M. Lagazio

Artificial Intelligence for Conflict Management

20 pages

cs.AI

Militarised conflict is one of the risks that have a significant impact on society. Militarised Interstate Dispute (MID) is defined as an outcome of interstate interactions, which result on either peace or conflict. Effective prediction of the possibility of conflict between states is an important decision support tool for policy makers. In a previous research, neural networks (NNs) have been implemented to predict the MID. Support Vector Machines (SVMs) have proven to be very good prediction techniques and are introduced for the prediction of MIDs in this study and compared to neural networks. The results show that SVMs predict MID better than NNs while NNs give more consistent and easy to interpret sensitivity analysis than SVMs.

0705.1244

Marc Schoenauer

Nicolas Godzik (INRIA Futurs, INRIA Rocquencourt), Marc Schoenauer (INRIA Futurs, INRIA Rocquencourt), Mich\`ele Sebag (INRIA Futurs, LRI)

Evolving Symbolic Controllers

Dans 4th European Workshop on Evolutionary Robotics, 2611 (2003) 638-650

cs.AI

The idea of symbolic controllers tries to bridge the gap between the top-down manual design of the controller architecture, as advocated in Brooks' subsumption architecture, and the bottom-up designer-free approach that is now standard within the Evolutionary Robotics community. The designer provides a set of elementary behavior, and evolution is given the goal of assembling them to solve complex tasks. Two experiments are presented, demonstrating the efficiency and showing the recursiveness of this approach. In particular, the sensitivity with respect to the proposed elementary behaviors, and the robustness w.r.t. generalization of the resulting controllers are studied in detail.

0705.1309

Marc Schoenauer

Alexandre Devert (INRIA Futurs), Nicolas Bred\`eche (INRIA Futurs), Marc Schoenauer (INRIA Futurs)

Robust Multi-Cellular Developmental Design

Dans Genetic and Evolutionary Computation COnference (2007)

cs.AI

This paper introduces a continuous model for Multi-cellular Developmental Design. The cells are fixed on a 2D grid and exchange "chemicals" with their neighbors during the growth process. The quantity of chemicals that a cell produces, as well as the differentiation value of the cell in the phenotype, are controlled by a Neural Network (the genotype) that takes as inputs the chemicals produced by the neighboring cells at the previous time step. In the proposed model, the number of iterations of the growth process is not pre-determined, but emerges during evolution: only organisms for which the growth process stabilizes give a phenotype (the stable state), others are declared nonviable. The optimization of the controller is done using the NEAT algorithm, that optimizes both the topology and the weights of the Neural Networks. Though each cell only receives local information from its neighbors, the experimental results of the proposed approach on the 'flags' problems (the phenotype must match a given 2D pattern) are almost as good as those of a direct regression approach using the same model with global information. Moreover, the resulting multi-cellular organisms exhibit almost perfect self-healing characteristics.

0705.2235

Tshilidzi Marwala

S. Chakraverty, T. Marwala, Pallavi Gupta and Thando Tettey

Response Prediction of Structural System Subject to Earthquake Motions using Artificial Neural Network

18 pages

cs.AI

This paper uses Artificial Neural Network (ANN) models to compute response of structural system subject to Indian earthquakes at Chamoli and Uttarkashi ground motion data. The system is first trained for a single real earthquake data. The trained ANN architecture is then used to simulate earthquakes with various intensities and it was found that the predicted responses given by ANN model are accurate for practical purposes. When the ANN is trained by a part of the ground motion data, it can also identify the responses of the structural system well. In this way the safeness of the structural systems may be predicted in case of future earthquakes without waiting for the earthquake to occur for the lessons. Time period and the corresponding maximum response of the building for an earthquake has been evaluated, which is again trained to predict the maximum response of the building at different time periods. The trained time period versus maximum response ANN model is also tested for real earthquake data of other place, which was not used in the training and was found to be in good agreement.

0705.2236

Tshilidzi Marwala

Tshilidzi Marwala, Thando Tettey and Snehashish Chakraverty

Fault Classification using Pseudomodal Energies and Neuro-fuzzy modelling

8 pages, In Proceedings of the Asia-Pacific Workshop on Structural Health Monitoring, Yokohama, Japan, 2006

cs.AI

This paper presents a fault classification method which makes use of a Takagi-Sugeno neuro-fuzzy model and Pseudomodal energies calculated from the vibration signals of cylindrical shells. The calculation of Pseudomodal Energies, for the purposes of condition monitoring, has previously been found to be an accurate method of extracting features from vibration signals. This calculation is therefore used to extract features from vibration signals obtained from a diverse population of cylindrical shells. Some of the cylinders in the population have faults in different substructures. The pseudomodal energies calculated from the vibration signals are then used as inputs to a neuro-fuzzy model. A leave-one-out cross-validation process is used to test the performance of the model. It is found that the neuro-fuzzy model is able to classify faults with an accuracy of 91.62%, which is higher than the previously used multilayer perceptron.

0705.2310

Tshilidzi Marwala

C.B. Vilakazi, T. Marwala, P. Mautla and E. Moloto

On-Line Condition Monitoring using Computational Intelligence

8 pages

cs.AI

This paper presents bushing condition monitoring frameworks that use multi-layer perceptrons (MLP), radial basis functions (RBF) and support vector machines (SVM) classifiers. The first level of the framework determines if the bushing is faulty or not while the second level determines the type of fault. The diagnostic gases in the bushings are analyzed using the dissolve gas analysis. MLP gives superior performance in terms of accuracy and training time than SVM and RBF. In addition, an on-line bushing condition monitoring approach, which is able to adapt to newly acquired data are introduced. This approach is able to accommodate new classes that are introduced by incoming data and is implemented using an incremental learning algorithm that uses MLP. The testing results improved from 67.5% to 95.8% as new data were introduced and the testing results improved from 60% to 95.3% as new conditions were introduced. On average the confidence value of the framework on its decision was 0.92.

0705.3360

Kyriakos Sgarbas

Kyriakos N. Sgarbas

The Road to Quantum Artificial Intelligence

9 pages. Presented at PCI-2007: 11th Panhellenic Conference in Informatics, 18-20 May 2007, Patras, Greece

In: T.S.Papatheodorou, D.N.Christodoulakis and N.N.Karanikolas (eds), "Current Trends in Informatics", Vol.A, pp.469-477, New Technologies Publications, Athens, 2007 (SET 978-960-89784-0-9)

cs.AI

This paper overviews the basic principles and recent advances in the emerging field of Quantum Computation (QC), highlighting its potential application to Artificial Intelligence (AI). The paper provides a very brief introduction to basic QC issues like quantum registers, quantum gates and quantum algorithms and then it presents references, ideas and research guidelines on how QC can be used to deal with some basic AI problems, such as search and pattern matching, as soon as quantum computers become widely available.

0705.4302

Jens Oehlschl\"agel

Jens Oehlschl\"agel

Truecluster matching

15 pages, 2 figures. Details the matching needed for "Truecluster: robust scalable clustering with model selection" but can also be used in different contexts

cs.AI

Cluster matching by permuting cluster labels is important in many clustering contexts such as cluster validation and cluster ensemble techniques. The classic approach is to minimize the euclidean distance between two cluster solutions which induces inappropriate stability in certain settings. Therefore, we present the truematch algorithm that introduces two improvements best explained in the crisp case. First, instead of maximizing the trace of the cluster crosstable, we propose to maximize a chi-square transformation of this crosstable. Thus, the trace will not be dominated by the cells with the largest counts but by the cells with the most non-random observations, taking into account the marginals. Second, we suggest a probabilistic component in order to break ties and to make the matching algorithm truly random on random data. The truematch algorithm is designed as a building block of the truecluster framework and scales in polynomial time. First simulation results confirm that the truematch algorithm gives more consistent truecluster results for unequal cluster sizes. Free R software is available.

0706.0022

Marko Antonio Rodriguez

Marko A. Rodriguez and Johan Bollen

Modeling Computations in a Semantic Network

project website: http://neno.lanl.gov

cs.AI

Semantic network research has seen a resurgence from its early history in the cognitive sciences with the inception of the Semantic Web initiative. The Semantic Web effort has brought forth an array of technologies that support the encoding, storage, and querying of the semantic network data structure at the world stage. Currently, the popular conception of the Semantic Web is that of a data modeling medium where real and conceptual entities are related in semantically meaningful ways. However, new models have emerged that explicitly encode procedural information within the semantic network substrate. With these new technologies, the Semantic Web has evolved from a data modeling medium to a computational medium. This article provides a classification of existing computational modeling efforts and the requirements of supporting technologies that will aid in the further growth of this burgeoning domain.

0706.1137

Thierry Poibeau

Amanda Bouffier (LIPN), Thierry Poibeau (LIPN)

Automatically Restructuring Practice Guidelines using the GEM DTD

Proceedings of Biomedical Natural Language Processing (BioNLP) (2007) -

cs.AI

This paper describes a system capable of semi-automatically filling an XML template from free texts in the clinical domain (practice guidelines). The XML template includes semantic information not explicitly encoded in the text (pairs of conditions and actions/recommendations). Therefore, there is a need to compute the exact scope of conditions over text sequences expressing the required actions. We present a system developed for this task. We show that it yields good performance when applied to the analysis of French practice guidelines.

0706.1290

Sylviane Schwer

Sylviane R. Schwer (LIPN)

Temporal Reasoning without Transitive Tables

rapport interne

cs.AI

Representing and reasoning about qualitative temporal information is an essential part of many artificial intelligence tasks. Lots of models have been proposed in the litterature for representing such temporal information. All derive from a point-based or an interval-based framework. One fundamental reasoning task that arises in applications of these frameworks is given by the following scheme: given possibly indefinite and incomplete knowledge of the binary relationships between some temporal objects, find the consistent scenarii between all these objects. All these models require transitive tables -- or similarly inference rules-- for solving such tasks. We have defined an alternative model, S-languages - to represent qualitative temporal information, based on the only two relations of \emph{precedence} and \emph{simultaneity}. In this paper, we show how this model enables to avoid transitive tables or inference rules to handle this kind of problem.

0706.3639

Marcus Hutter

Shane Legg and Marcus Hutter

A Collection of Definitions of Intelligence

12 LaTeX pages

Frontiers in Artificial Intelligence and Applications, Vol.157 (2007) 17-24

IDSIA-07-07

cs.AI

This paper is a survey of a large number of informal definitions of ``intelligence'' that the authors have collected over the years. Naturally, compiling a complete list would be impossible as many definitions of intelligence are buried deep inside articles and books. Nevertheless, the 70-odd definitions presented here are, to the authors' knowledge, the largest and most well referenced collection there is.

0706.4375

Thierry Hamon

Thierry Hamon (LIPN), Adeline Nazarenko (LIPN), Thierry Poibeau (LIPN), Sophie Aubin (LIPN), Julien Derivi\`ere (LIPN)

A Robust Linguistic Platform for Efficient and Domain specific Web Content Analysis

Proceedings of RIAO 2007 (30/05/2007)

cs.AI

Web semantic access in specific domains calls for specialized search engines with enhanced semantic querying and indexing capacities, which pertain both to information retrieval (IR) and to information extraction (IE). A rich linguistic analysis is required either to identify the relevant semantic units to index and weight them according to linguistic specific statistical distribution, or as the basis of an information extraction process. Recent developments make Natural Language Processing (NLP) techniques reliable enough to process large collections of documents and to enrich them with semantic annotations. This paper focuses on the design and the development of a text processing platform, Ogmios, which has been developed in the ALVIS project. The Ogmios platform exploits existing NLP modules and resources, which may be tuned to specific domains and produces linguistically annotated documents. We show how the three constraints of genericity, domain semantic awareness and performance can be handled all together.

0707.2506

Alain Dutech

Raghav Aras (INRIA Lorraine - LORIA), Alain Dutech (INRIA Lorraine - LORIA), Fran\c{c}ois Charpillet (INRIA Lorraine - LORIA)

Mixed Integer Linear Programming For Exact Finite-Horizon Planning In Decentralized Pomdps

Dans The International Conference on Automated Planning and Scheduling (2007)

cs.AI

We consider the problem of finding an n-agent joint-policy for the optimal finite-horizon control of a decentralized Pomdp (Dec-Pomdp). This is a problem of very high complexity (NEXP-hard in n >= 2). In this paper, we propose a new mathematical programming approach for the problem. Our approach is based on two ideas: First, we represent each agent's policy in the sequence-form and not in the tree-form, thereby obtaining a very compact representation of the set of joint-policies. Second, using this compact representation, we solve this problem as an instance of combinatorial optimization for which we formulate a mixed integer linear program (MILP). The optimal solution of the MILP directly yields an optimal joint-policy for the Dec-Pomdp. Computational experience shows that formulating and solving the MILP requires significantly less time to solve benchmark Dec-Pomdp problems than existing algorithms. For example, the multi-agent tiger problem for horizon 4 is solved in 72 secs with the MILP whereas existing algorithms require several hours to solve it.

0707.4289

Sheng Bao

Stephen Gang Wu, Forrest Sheng Bao, Eric You Xu, Yu-Xuan Wang, Yi-Fan Chang and Qiao-Liang Xiang

A Leaf Recognition Algorithm for Plant Classification Using Probabilistic Neural Network

6 pages, 3 figures, 2 tables

cs.AI

In this paper, we employ Probabilistic Neural Network (PNN) with image and data processing techniques to implement a general purpose automated leaf recognition algorithm. 12 leaf features are extracted and orthogonalized into 5 principal variables which consist the input vector of the PNN. The PNN is trained by 1800 leaves to classify 32 kinds of plants with an accuracy greater than 90%. Compared with other approaches, our algorithm is an accurate artificial intelligence approach which is fast in execution and easy in implementation.

0708.4311

Juergen Schmidhuber

Juergen Schmidhuber

2006: Celebrating 75 years of AI - History and Outlook: the Next 25 Years

14 pages; preprint of invited contribution to the Proceedings of the ``50th Anniversary Summit of Artificial Intelligence'' at Monte Verita, Ascona, Switzerland, 9-14 July 2006

cs.AI

When Kurt Goedel layed the foundations of theoretical computer science in 1931, he also introduced essential concepts of the theory of Artificial Intelligence (AI). Although much of subsequent AI research has focused on heuristics, which still play a major role in many practical AI applications, in the new millennium AI theory has finally become a full-fledged formal science, with important optimality results for embodied agents living in unknown environments, obtained through a combination of theory a la Goedel and probability theory. Here we look back at important milestones of AI history, mention essential recent results, and speculate about what we may expect from the next 25 years, emphasizing the significance of the ongoing dramatic hardware speedups, and discussing Goedel-inspired, self-referential, self-improving universal problem solvers.

0709.0522

Florentin Smarandache

Florentin Smarandache, Jean Dezert

Qualitative Belief Conditioning Rules (QBCR)

13 pages. Presented at Fusion 2007 International Conference, Quebec City, Canada, July 2007

Proceedings of Fusion 2007 International Conference, Quebec City, Canada, July 2007

cs.AI

In this paper we extend the new family of (quantitative) Belief Conditioning Rules (BCR) recently developed in the Dezert-Smarandache Theory (DSmT) to their qualitative counterpart for belief revision. Since the revision of quantitative as well as qualitative belief assignment given the occurrence of a new event (the conditioning constraint) can be done in many possible ways, we present here only what we consider as the most appealing Qualitative Belief Conditioning Rules (QBCR) which allow to revise the belief directly with words and linguistic labels and thus avoids the introduction of ad-hoc translations of quantitative beliefs into quantitative ones for solving the problem.

0709.1167

Marko Antonio Rodriguez

Marko A. Rodriguez, Jennifer H. Watkins, Johan Bollen, Carlos Gershenson

Using RDF to Model the Structure and Process of Systems

International Conference on Complex Systems, Boston MA, October 2007

InterJournal of Complex Systems, 2131, ISSN: 1081-0625, February 2008

LAUR-07-5720

cs.AI

Many systems can be described in terms of networks of discrete elements and their various relationships to one another. A semantic network, or multi-relational network, is a directed labeled graph consisting of a heterogeneous set of entities connected by a heterogeneous set of relationships. Semantic networks serve as a promising general-purpose modeling substrate for complex systems. Various standardized formats and tools are now available to support practical, large-scale semantic network models. First, the Resource Description Framework (RDF) offers a standardized semantic network data model that can be further formalized by ontology modeling languages such as RDF Schema (RDFS) and the Web Ontology Language (OWL). Second, the recent introduction of highly performant triple-stores (i.e. semantic network databases) allows semantic network models on the order of $10^9$ edges to be efficiently stored and manipulated. RDF and its related technologies are currently used extensively in the domains of computer science, digital library science, and the biological sciences. This article will provide an introduction to RDF/RDFS/OWL and an examination of its suitability to model discrete element complex systems.

0709.1701

Jean Dezert

Xinde Li (ICRL), Xinhan Huang (ICRL), Florentin Smarandache (UNM), Jean Dezert (ONERA)

Enrichment of Qualitative Beliefs for Reasoning under Uncertainty

12 pages

cs.AI

This paper deals with enriched qualitative belief functions for reasoning under uncertainty and for combining information expressed in natural language through linguistic labels. In this work, two possible enrichments (quantitative and/or qualitative) of linguistic labels are considered and operators (addition, multiplication, division, etc) for dealing with them are proposed and explained. We denote them $qe$-operators, $qe$ standing for "qualitative-enriched" operators. These operators can be seen as a direct extension of the classical qualitative operators ($q$-operators) proposed recently in the Dezert-Smarandache Theory of plausible and paradoxist reasoning (DSmT). $q$-operators are also justified in details in this paper. The quantitative enrichment of linguistic label is a numerical supporting degree in $[0,\infty)$, while the qualitative enrichment takes its values in a finite ordered set of linguistic values. Quantitative enrichment is less precise than qualitative enrichment, but it is expected more close with what human experts can easily provide when expressing linguistic labels with supporting degrees. Two simple examples are given to show how the fusion of qualitative-enriched belief assignments can be done.

0709.2065

Andrei Khrennikov

Andrei Khrennikov

Toward Psycho-robots

Paladyn Volume 1, Number 2, 99-108, 2010

10.2478/s13230-010-0014-0

cs.AI

We try to perform geometrization of psychology by representing mental states, <<ideas>>, by points of a metric space, <<mental space>>. Evolution of ideas is described by dynamical systems in metric mental space. We apply the mental space approach for modeling of flows of unconscious and conscious information in the human brain. In a series of models, Models 1-4, we consider cognitive systems with increasing complexity of psychological behavior determined by structure of flows of ideas. Since our models are in fact models of the AI-type, one immediately recognizes that they can be used for creation of AI-systems, which we call psycho-robots, exhibiting important elements of human psyche. Creation of such psycho-robots may be useful improvement of domestic robots. At the moment domestic robots are merely simple working devices (e.g. vacuum cleaners or lawn mowers) . However, in future one can expect demand in systems which be able not only perform simple work tasks, but would have elements of human self-developing psyche. Such AI-psyche could play an important role both in relations between psycho-robots and their owners as well as between psycho-robots. Since the presence of a huge numbers of psycho-complexes is an essential characteristic of human psychology, it would be interesting to model them in the AI-framework.

0709.3974

Sebastien Verel

S\'ebastien Verel (I3S), Philippe Collard (I3S), Marco Tomassini (ISI), Leonardo Vanneschi (DISCO)

Fitness landscape of the cellular automata majority problem: View from the Olympus

Theoretical Computer Science 378, 1 (2007) 54-77

10.1016/j.tcs.2007.01.001

cs.AI

In this paper we study cellular automata (CAs) that perform the computational Majority task. This task is a good example of what the phenomenon of emergence in complex systems is. We take an interest in the reasons that make this particular fitness landscape a difficult one. The first goal is to study the landscape as such, and thus it is ideally independent from the actual heuristics used to search the space. However, a second goal is to understand the features a good search technique for this particular problem space should possess. We statistically quantify in various ways the degree of difficulty of searching this landscape. Due to neutrality, investigations based on sampling techniques on the whole landscape are difficult to conduct. So, we go exploring the landscape from the top. Although it has been proved that no CA can perform the task perfectly, several efficient CAs for this task have been found. Exploiting similarities between these CAs and symmetries in the landscape, we define the Olympus landscape which is regarded as the ''heavenly home'' of the best local optima known (blok). Then we measure several properties of this subspace. Although it is easier to find relevant CAs in this subspace than in the overall landscape, there are structural reasons that prevent a searcher from finding overfitted CAs in the Olympus. Finally, we study dynamics and performance of genetic algorithms on the Olympus in order to confirm our analysis and to find efficient CAs for the Majority problem with low computational cost.

0709.4010

Sebastien Verel

Philippe Collard (I3S), S\'ebastien Verel (I3S), Manuel Clergue (I3S)

Local search heuristics: Fitness Cloud versus Fitness Landscape

Dans Poster at the 2004 European Conference on Artificial Intelligence (ECAI04) - the 2004 European Conference on Artificial Intelligence (ECAI04), Valencia : Espagne (2004)

cs.AI

This paper introduces the concept of fitness cloud as an alternative way to visualize and analyze search spaces than given by the geographic notion of fitness landscape. It is argued that the fitness cloud concept overcomes several deficiencies of the landscape representation. Our analysis is based on the correlation between fitness of solutions and fitnesses of nearest solutions according to some neighboring. We focus on the behavior of local search heuristics, such as hill climber, on the well-known NK fitness landscape. In both cases the fitness vs. fitness correlation is shown to be related to the epistatic parameter K.

0709.4011

Sebastien Verel

S\'ebastien Verel (I3S), Philippe Collard (I3S), Manuel Clergue (I3S)

Measuring the Evolvability Landscape to study Neutrality

Dans Poster at Genetic and Evolutionary Computation -- GECCO-2006 - Genetic and Evolutionary Computation -- GECCO-2006, Seattle, WA : \'Etats-Unis d'Am\'erique (2006)

cs.AI

This theoretical work defines the measure of autocorrelation of evolvability in the context of neutral fitness landscape. This measure has been studied on the classical MAX-SAT problem. This work highlight a new characteristic of neutral fitness landscapes which allows to design new adapted metaheuristic.

0709.4015

Amanda Bouffier

Amanda Bouffier (LIPN)

From Texts to Structured Documents: The Case of Health Practice Guidelines

Dans International Semantic Web Conference Proceedings - International Semantic Web Conference-Doctoral Consortium, Busan : Cor\'ee, R\'epublique de (2007)

10.1007/978-3-540-76298-0_69

cs.AI

This paper describes a system capable of semi-automatically filling an XML template from free texts in the clinical domain (practice guidelines). The XML template includes semantic information not explicitly encoded in the text (pairs of conditions and actions/recommendations). Therefore, there is a need to compute the exact scope of conditions over text sequences expressing the required actions. We present in this paper the rules developed for this task. We show that the system yields good performance when applied to the analysis of French practice guidelines.

0710.0013

Jason Johnson

Jason K. Johnson, Dmitry M. Malioutov, Alan S. Willsky

Lagrangian Relaxation for MAP Estimation in Graphical Models

10 pages, presented at 45th Allerton conference on communication, control and computing, to appear in proceedings

cs.AI

We develop a general framework for MAP estimation in discrete and Gaussian graphical models using Lagrangian relaxation techniques. The key idea is to reformulate an intractable estimation problem as one defined on a more tractable graph, but subject to additional constraints. Relaxing these constraints gives a tractable dual problem, one defined by a thin graph, which is then optimized by an iterative procedure. When this iterative optimization leads to a consistent estimate, one which also satisfies the constraints, then it corresponds to an optimal MAP estimate of the original model. Otherwise there is a ``duality gap'', and we obtain a bound on the optimal solution. Thus, our approach combines convex optimization with dynamic programming techniques applicable for thin graphs. The popular tree-reweighted max-product (TRMP) method may be seen as solving a particular class of such relaxations, where the intractable graph is relaxed to a set of spanning trees. We also consider relaxations to a set of small induced subgraphs, thin subgraphs (e.g. loops), and a connected tree obtained by ``unwinding'' cycles. In addition, we propose a new class of multiscale relaxations that introduce ``summary'' variables. The potential benefits of such generalizations include: reducing or eliminating the ``duality gap'' in hard problems, reducing the number or Lagrange multipliers in the dual problem, and accelerating convergence of the iterative optimization procedure.

0710.4231

Yoshiharu Maeno

Yoshiharu Maeno, and Yukio Ohsawa

Analyzing covert social network foundation behind terrorism disaster

17pages, 10 figures, submitted to Int. J. Services Sciences

International Journal of Services Sciences Vol.2, pp.125-141 (2009)

10.1504/IJSSCI.2009.024936

cs.AI

This paper addresses a method to analyze the covert social network foundation hidden behind the terrorism disaster. It is to solve a node discovery problem, which means to discover a node, which functions relevantly in a social network, but escaped from monitoring on the presence and mutual relationship of nodes. The method aims at integrating the expert investigator's prior understanding, insight on the terrorists' social network nature derived from the complex graph theory, and computational data processing. The social network responsible for the 9/11 attack in 2001 is used to execute simulation experiment to evaluate the performance of the method.

0710.4975

Yoshiharu Maeno

Yoshiharu Maeno

Node discovery problem for a social network

Connections vol.29, pp.62-76 (2009)

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Methods to solve a node discovery problem for a social network are presented. Covert nodes refer to the nodes which are not observable directly. They transmit the influence and affect the resulting collaborative activities among the persons in a social network, but do not appear in the surveillance logs which record the participants of the collaborative activities. Discovering the covert nodes is identifying the suspicious logs where the covert nodes would appear if the covert nodes became overt. The performance of the methods is demonstrated with a test dataset generated from computationally synthesized networks and a real organization.

0711.1466

Yoshiharu Maeno

Yoshiharu Maeno and Yukio Ohsawa

Predicting relevant empty spots in social interaction

11 pages, 5 figures, submitted to J. Systems Science and Complexity

Journal of Systems Science and Complexity vol.21, pp.161-171 (2008)

cs.AI

An empty spot refers to an empty hard-to-fill space which can be found in the records of the social interaction, and is the clue to the persons in the underlying social network who do not appear in the records. This contribution addresses a problem to predict relevant empty spots in social interaction. Homogeneous and inhomogeneous networks are studied as a model underlying the social interaction. A heuristic predictor function approach is presented as a new method to address the problem. Simulation experiment is demonstrated over a homogeneous network. A test data in the form of baskets is generated from the simulated communication. Precision to predict the empty spots is calculated to demonstrate the performance of the presented approach.

0711.3419

Leo Obrst

Ken Samuel, Leo Obrst, Suzette Stoutenberg, Karen Fox, Paul Franklin, Adrian Johnson, Ken Laskey, Deborah Nichols, Steve Lopez, Jason Peterson

Translating OWL and Semantic Web Rules into Prolog: Moving Toward Description Logic Programs

21 pages, 5 figures, 19 tables. To appear in Theory and Practice of Logic Programming (TPLP), 2008

cs.AI

To appear in Theory and Practice of Logic Programming (TPLP), 2008. We are researching the interaction between the rule and the ontology layers of the Semantic Web, by comparing two options: 1) using OWL and its rule extension SWRL to develop an integrated ontology/rule language, and 2) layering rules on top of an ontology with RuleML and OWL. Toward this end, we are developing the SWORIER system, which enables efficient automated reasoning on ontologies and rules, by translating all of them into Prolog and adding a set of general rules that properly capture the semantics of OWL. We have also enabled the user to make dynamic changes on the fly, at run time. This work addresses several of the concerns expressed in previous work, such as negation, complementary classes, disjunctive heads, and cardinality, and it discusses alternative approaches for dealing with inconsistencies in the knowledge base. In addition, for efficiency, we implemented techniques called extensionalization, avoiding reanalysis, and code minimization.

0712.0836

Andrew Adamatzky

Andrew Adamatzky, Larry Bull, Pierre Collet, Emmanuel Sapin

Evolving localizations in reaction-diffusion cellular automata

Accepted for publication in Int. J. Modern Physics C

International Journal of Modern Physics C (IJMPC) Volume: 19, Issue: 4 (April 2008) pp. 557-567

10.1142/S0129183108012376

cs.AI

We consider hexagonal cellular automata with immediate cell neighbourhood and three cell-states. Every cell calculates its next state depending on the integral representation of states in its neighbourhood, i.e. how many neighbours are in each one state. We employ evolutionary algorithms to breed local transition functions that support mobile localizations (gliders), and characterize sets of the functions selected in terms of quasi-chemical systems. Analysis of the set of functions evolved allows to speculate that mobile localizations are likely to emerge in the quasi-chemical systems with limited diffusion of one reagent, a small number of molecules is required for amplification of travelling localizations, and reactions leading to stationary localizations involve relatively equal amount of quasi-chemical species. Techniques developed can be applied in cascading signals in nature-inspired spatially extended computing devices, and phenomenological studies and classification of non-linear discrete systems.

0712.2389

Guido Tack

Martin Mann and Guido Tack and Sebastian Will

Decomposition During Search for Propagation-Based Constraint Solvers

20 pages, 9 figures, 2 tables; longer, more detailed version

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

We describe decomposition during search (DDS), an integration of And/Or tree search into propagation-based constraint solvers. The presented search algorithm dynamically decomposes sub-problems of a constraint satisfaction problem into independent partial problems, avoiding redundant work. The paper discusses how DDS interacts with key features that make propagation-based solvers successful: constraint propagation, especially for global constraints, and dynamic search heuristics. We have implemented DDS for the Gecode constraint programming library. Two applications, solution counting in graph coloring and protein structure prediction, exemplify the benefits of DDS in practice.

0712.3329

Marcus Hutter

Shane Legg and Marcus Hutter

Universal Intelligence: A Definition of Machine Intelligence

50 gentle pages

Minds & Machines, 17:4 (2007) pages 391-444

IDSIA-10-07

cs.AI

A fundamental problem in artificial intelligence is that nobody really knows what intelligence is. The problem is especially acute when we need to consider artificial systems which are significantly different to humans. In this paper we approach this problem in the following way: We take a number of well known informal definitions of human intelligence that have been given by experts, and extract their essential features. These are then mathematically formalised to produce a general measure of intelligence for arbitrary machines. We believe that this equation formally captures the concept of machine intelligence in the broadest reasonable sense. We then show how this formal definition is related to the theory of universal optimal learning agents. Finally, we survey the many other tests and definitions of intelligence that have been proposed for machines.

0712.3825

Marcus Hutter

Shane Legg and Marcus Hutter

Tests of Machine Intelligence

12 pages; 1 table. Turing test and derivatives; Compression tests; Linguistic complexity; Multiple cognitive abilities; Competitive games; Psychometric tests; Smith's test; C-test; Universal intelligence

50 Years of Artificial Intelligence (2007) pages 232-242

IDSIA-11-07

cs.AI

Although the definition and measurement of intelligence is clearly of fundamental importance to the field of artificial intelligence, no general survey of definitions and tests of machine intelligence exists. Indeed few researchers are even aware of alternatives to the Turing test and its many derivatives. In this paper we fill this gap by providing a short survey of the many tests of machine intelligence that have been proposed.

0712.4318

Peter de Blanc

Peter de Blanc

Convergence of Expected Utilities with Algorithmic Probability Distributions

2 pages + title page, references

cs.AI

We consider an agent interacting with an unknown environment. The environment is a function which maps natural numbers to natural numbers; the agent's set of hypotheses about the environment contains all such functions which are computable and compatible with a finite set of known input-output pairs, and the agent assigns a positive probability to each such hypothesis. We do not require that this probability distribution be computable, but it must be bounded below by a positive computable function. The agent has a utility function on outputs from the environment. We show that if this utility function is bounded below in absolute value by an unbounded computable function, then the expected utility of any input is undefined. This implies that a computable utility function will have convergent expected utilities iff that function is bounded.

0801.1275

Christophe Roche

Christophe Roche (LISTIC)

Le terme et le concept : fondements d'une ontoterminologie

22 pages

Dans TOTh 2007 : Terminologie et Ontologie : Th\'eories et Applications - TOTh 2007 : Terminologie et Ontologie : Th\'eories et Applications, Annecy : France (2007)

cs.AI

Most definitions of ontology, viewed as a "specification of a conceptualization", agree on the fact that if an ontology can take different forms, it necessarily includes a vocabulary of terms and some specification of their meaning in relation to the domain's conceptualization. And as domain knowledge is mainly conveyed through scientific and technical texts, we can hope to extract some useful information from them for building ontology. But is it as simple as this? In this article we shall see that the lexical structure, i.e. the network of words linked by linguistic relationships, does not necessarily match the domain conceptualization. We have to bear in mind that writing documents is the concern of textual linguistics, of which one of the principles is the incompleteness of text, whereas building ontology - viewed as task-independent knowledge - is concerned with conceptualization based on formal and not natural languages. Nevertheless, the famous Sapir and Whorf hypothesis, concerning the interdependence of thought and language, is also applicable to formal languages. This means that the way an ontology is built and a concept is defined depends directly on the formal language which is used; and the results will not be the same. The introduction of the notion of ontoterminology allows to take into account epistemological principles for formal ontology building.

0801.1336

Subhash Kak

Subhash Kak

Stream Computing

7 pages, 4 figures

cs.AI

Stream computing is the use of multiple autonomic and parallel modules together with integrative processors at a higher level of abstraction to embody "intelligent" processing. The biological basis of this computing is sketched and the matter of learning is examined.

0802.2429

Sebastien Verel

David Simoncini (I3S), S\'ebastien Verel (I3S), Philippe Collard (I3S), Manuel Clergue (I3S)

Anisotropic selection in cellular genetic algorithms

Dans Proceedings of the 8th annual conference on Genetic and evolutionary computation - Genetic And Evolutionary Computation Conference, Seatle : \'Etats-Unis d'Am\'erique (2006)

10.1145/1143997.1144098

cs.AI

In this paper we introduce a new selection scheme in cellular genetic algorithms (cGAs). Anisotropic Selection (AS) promotes diversity and allows accurate control of the selective pressure. First we compare this new scheme with the classical rectangular grid shapes solution according to the selective pressure: we can obtain the same takeover time with the two techniques although the spreading of the best individual is different. We then give experimental results that show to what extent AS promotes the emergence of niches that support low coupling and high cohesion. Finally, using a cGA with anisotropic selection on a Quadratic Assignment Problem we show the existence of an anisotropic optimal value for which the best average performance is observed. Further work will focus on the selective pressure self-adjustment ability provided by this new selection scheme.

0803.1087

Cl\'ement Vidal

Clement Vidal

The Future of Scientific Simulations: from Artificial Life to Artificial Cosmogenesis

The text was improved in many respects, and a new figure was added. Cite as: Vidal, C. 2008. The Future of Scientific Simulations: from Artificial Life to Artificial Cosmogenesis. In Death And Anti-Death, Volume 6: Thirty Years After Kurt Godel (1906-1978), Ed. Charles Tandy, in press

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

This philosophical paper explores the relation between modern scientific simulations and the future of the universe. We argue that a simulation of an entire universe will result from future scientific activity. This requires us to tackle the challenge of simulating open-ended evolution at all levels in a single simulation. The simulation should encompass not only biological evolution, but also physical evolution (a level below) and cultural evolution (a level above). The simulation would allow us to probe what would happen if we would "replay the tape of the universe" with the same or different laws and initial conditions. We also distinguish between real-world and artificial-world modelling. Assuming that intelligent life could indeed simulate an entire universe, this leads to two tentative hypotheses. Some authors have argued that we may already be in a simulation run by an intelligent entity. Or, if such a simulation could be made real, this would lead to the production of a new universe. This last direction is argued with a careful speculative philosophical approach, emphasizing the imperative to find a solution to the heat death problem in cosmology. The reader is invited to consult Annex 1 for an overview of the logical structure of this paper. -- Keywords: far future, future of science, ALife, simulation, realization, cosmology, heat death, fine-tuning, physical eschatology, cosmological natural selection, cosmological artificial selection, artificial cosmogenesis, selfish biocosm hypothesis, meduso-anthropic principle, developmental singularity hypothesis, role of intelligent life.

0803.1207

Hang Dinh

Hang Dinh

Serious Flaws in Korf et al.'s Analysis on Time Complexity of A*

This paper has been withdrawn

cs.AI

http://creativecommons.org/licenses/by/3.0/

This paper has been withdrawn.

0803.3192

Denis Pallez

Denis Pallez (LIRIS), Philippe Collard (I3S), Thierry Baccino (LPEQ), Laurent Dumercy (LPEQ)

Eye-Tracking Evolutionary Algorithm to minimize user's fatigue in IEC applied to Interactive One-Max problem

Dans Proceedings of the 2007 GECCO conference companion on Genetic and evolutionary computation - GECCO '07: the 2007 GECCO conference companion on Genetic and evolutionary computation, London : Royaume-Uni (2007)

10.1145/1274000.1274098

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

In this paper, we describe a new algorithm that consists in combining an eye-tracker for minimizing the fatigue of a user during the evaluation process of Interactive Evolutionary Computation. The approach is then applied to the Interactive One-Max optimization problem.

0803.3363

Yoshiharu Maeno

Yoshiharu Maeno

Node discovery in a networked organization

Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, San Antonio, October 2009

10.1109/ICSMC.2009.5346826

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

In this paper, I present a method to solve a node discovery problem in a networked organization. Covert nodes refer to the nodes which are not observable directly. They affect social interactions, but do not appear in the surveillance logs which record the participants of the social interactions. Discovering the covert nodes is defined as identifying the suspicious logs where the covert nodes would appear if the covert nodes became overt. A mathematical model is developed for the maximal likelihood estimation of the network behind the social interactions and for the identification of the suspicious logs. Precision, recall, and F measure characteristics are demonstrated with the dataset generated from a real organization and the computationally synthesized datasets. The performance is close to the theoretical limit for any covert nodes in the networks of any topologies and sizes if the ratio of the number of observation to the number of possible communication patterns is large.

0803.3501

Fahem Kebair

Fahem Kebair (LITIS), Fr\'ed\'eric Serin (LITIS)

Multiagent Approach for the Representation of Information in a Decision Support System

Multiagent Approach for the Representation of Information in a Decision Support System, Springer Berlin / Heidelberg (Ed.) (2006) 98-107

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

In an emergency situation, the actors need an assistance allowing them to react swiftly and efficiently. In this prospect, we present in this paper a decision support system that aims to prepare actors in a crisis situation thanks to a decision-making support. The global architecture of this system is presented in the first part. Then we focus on a part of this system which is designed to represent the information of the current situation. This part is composed of a multiagent system that is made of factual agents. Each agent carries a semantic feature and aims to represent a partial part of a situation. The agents develop thanks to their interactions by comparing their semantic features using proximity measures and according to specific ontologies.

0803.4074

Yoshiharu Maeno

Yoshiharu Maeno and Yukio Ohsawa

Reflective visualization and verbalization of unconscious preference

This will be submitted to KES Journal

International Journal of Advanced Intelligence Paradigms Vol.2, pp.125-139 (2010)

10.1504/IJAIP.2010.030531

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

A new method is presented, that can help a person become aware of his or her unconscious preferences, and convey them to others in the form of verbal explanation. The method combines the concepts of reflection, visualization, and verbalization. The method was tested in an experiment where the unconscious preferences of the subjects for various artworks were investigated. In the experiment, two lessons were learned. The first is that it helps the subjects become aware of their unconscious preferences to verbalize weak preferences as compared with strong preferences through discussion over preference diagrams. The second is that it is effective to introduce an adjustable factor into visualization to adapt to the differences in the subjects and to foster their mutual understanding.

0804.0528

\^Hamed \"Owladeghaffari

H.Owladeghaffari, M.Ejtemaei, M.Irannajad

Application of Rough Set Theory to Analysis of Hydrocyclone Operation

InternationalConference on Smart Materials and Adaptive Structures: Mathematical Modeling and Computation

cs.AI

http://creativecommons.org/licenses/by/3.0/

This paper describes application of rough set theory, on the analysis of hydrocyclone operation. In this manner, using Self Organizing Map (SOM) as preprocessing step, best crisp granules of data are obtained. Then, using a combining of SOM and rough set theory (RST)-called SORST-, the dominant rules on the information table, obtained from laboratory tests, are extracted. Based on these rules, an approximate estimation on decision attribute is fulfilled. Finally, a brief comparison of this method with the SOM-NFIS system (briefly SONFIS) is highlighted.

0804.0558

Fahem Kebair

Fahem Kebair (LITIS), Fr\'ed\'eric Serin (LITIS), Cyrille Bertelle (LITIS)

Agent-Based Perception of an Environment in an Emergency Situation

Dans Proceedings of the World Congress on Engineering - Proceedings of the World Congress on Engineering, London : Royaume-Uni (2007)

10.1007/978-988-98671-5-7,978-988-98671-2-6

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

We are interested in the problem of multiagent systems development for risk detecting and emergency response in an uncertain and partially perceived environment. The evaluation of the current situation passes by three stages inside the multiagent system. In a first time, the situation is represented in a dynamic way. The second step, consists to characterise the situation and finally, it is compared with other similar known situations. In this paper, we present an information modelling of an observed environment, that we have applied on the RoboCupRescue Simulation System. Information coming from the environment are formatted according to a taxonomy and using semantic features. The latter are defined thanks to a fine ontology of the domain and are managed by factual agents that aim to represent dynamically the current situation.

0804.0852

Sebastien Verel

David Simoncini (I3S), Philippe Collard (I3S), S\'ebastien Verel (I3S), Manuel Clergue (I3S)

On the Influence of Selection Operators on Performances in Cellular Genetic Algorithms

Dans Proceedings of the IEEE Congress on Evolutionary Computation CEC2007 - IEEE Congress on Evolutionary Computation CEC2007, singapore : Singapour (2007)

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

In this paper, we study the influence of the selective pressure on the performance of cellular genetic algorithms. Cellular genetic algorithms are genetic algorithms where the population is embedded on a toroidal grid. This structure makes the propagation of the best so far individual slow down, and allows to keep in the population potentially good solutions. We present two selective pressure reducing strategies in order to slow down even more the best solution propagation. We experiment these strategies on a hard optimization problem, the quadratic assignment problem, and we show that there is a value for of the control parameter for both which gives the best performance. This optimal value does not find explanation on only the selective pressure, measured either by take over time and diversity evolution. This study makes us conclude that we need other tools than the sole selective pressure measures to explain the performances of cellular genetic algorithms.

0804.1244

Fionn Murtagh

Fionn Murtagh

Geometric Data Analysis, From Correspondence Analysis to Structured Data Analysis (book review)

5 pages, 8 citations. Accepted in Journal of Classification

Journal of Classification 25, 137-141, 2008

10.1007/s00357-008-9007-7

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Review of: Brigitte Le Roux and Henry Rouanet, Geometric Data Analysis, From Correspondence Analysis to Structured Data Analysis, Kluwer, Dordrecht, 2004, xi+475 pp.

0805.0459

\^Hamed \"Owladeghaffari

Hamed Owladeghaffari

Phase transition in SONFIS&SORST

submitted to :The Sixth International Conference on Rough Sets and Current Trends in Computing; Akron, Ohio, USA,2008

10.1007/978-3-540-88425-5_35

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

In this study, we introduce general frame of MAny Connected Intelligent Particles Systems (MACIPS). Connections and interconnections between particles get a complex behavior of such merely simple system (system in system).Contribution of natural computing, under information granulation theory, are the main topics of this spacious skeleton. Upon this clue, we organize two algorithms involved a few prominent intelligent computing and approximate reasoning methods: self organizing feature map (SOM), Neuro- Fuzzy Inference System and Rough Set Theory (RST). Over this, we show how our algorithms can be taken as a linkage of government-society interaction, where government catches various fashions of behavior: solid (absolute) or flexible. So, transition of such society, by changing of connectivity parameters (noise) from order to disorder is inferred. Add to this, one may find an indirect mapping among financial systems and eventual market fluctuations with MACIPS. Keywords: phase transition, SONFIS, SORST, many connected intelligent particles system, society-government interaction

0805.1096

Kaijun Wang Mr.

Kaijun Wang, Junying Zhang, Dan Li, Xinna Zhang and Tao Guo

Adaptive Affinity Propagation Clustering

an English version of original paper

K. Wang, J. Zhang, D. Li, X. Zhang and T. Guo. Adaptive Affinity Propagation Clustering. Acta Automatica Sinica, 33(12):1242-1246, 2007

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Affinity propagation clustering (AP) has two limitations: it is hard to know what value of parameter 'preference' can yield an optimal clustering solution, and oscillations cannot be eliminated automatically if occur. The adaptive AP method is proposed to overcome these limitations, including adaptive scanning of preferences to search space of the number of clusters for finding the optimal clustering solution, adaptive adjustment of damping factors to eliminate oscillations, and adaptive escaping from oscillations when the damping adjustment technique fails. Experimental results on simulated and real data sets show that the adaptive AP is effective and can outperform AP in quality of clustering results.

0805.1288

\^Hamed \"Owladeghaffari

H. Owladeghaffari, K. Shahriar, G. H. R. Saeedi

Assessment of effective parameters on dilution using approximate reasoning methods in longwall mining method, Iran coal mines

9 Pages,9 Figures,submitted to :The 21st World Mining Congress &EXPO 2008; 7-11 ;September 2008,;Krakow, Poland

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Approximately more than 90% of all coal production in Iranian underground mines is derived directly longwall mining method. Out of seam dilution is one of the essential problems in these mines. Therefore the dilution can impose the additional cost of mining and milling. As a result, recognition of the effective parameters on the dilution has a remarkable role in industry. In this way, this paper has analyzed the influence of 13 parameters (attributed variables) versus the decision attribute (dilution value), so that using two approximate reasoning methods, namely Rough Set Theory (RST) and Self Organizing Neuro- Fuzzy Inference System (SONFIS) the best rules on our collected data sets has been extracted. The other benefit of later methods is to predict new unknown cases. So, the reduced sets (reducts) by RST have been obtained. Therefore the emerged results by utilizing mentioned methods shows that the high sensitive variables are thickness of layer, length of stope, rate of advance, number of miners, type of advancing.

0805.2308

\^Hamed \"Owladeghaffari

H.Owladeghaffari

Toward Fuzzy block theory

8 PAGES,7 FIGURES

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

This study, fundamentals of fuzzy block theory, and its application in assessment of stability in underground openings, has surveyed. Using fuzzy topics and inserting them in to key block theory, in two ways, fundamentals of fuzzy block theory has been presented. In indirect combining, by coupling of adaptive Neuro Fuzzy Inference System (NFIS) and classic block theory, we could extract possible damage parts around a tunnel. In direct solution, some principles of block theory, by means of different fuzzy facets theory, were rewritten.

0805.2440

\^Hamed \"Owladeghaffari

Hamed Owladeghaffari, Majid Ejtemaei, Mehdi Irannajad

Analysis of hydrocyclone performance based on information granulation theory

8th. World Congress on Computational Mechanics (WCCM8) 5th. European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2008) 2008 Venice, Italy

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

This paper describes application of information granulation theory, on the analysis of hydrocyclone perforamance. In this manner, using a combining of Self Organizing Map (SOM) and Neuro-Fuzzy Inference System (NFIS), crisp and fuzzy granules are obtained(briefly called SONFIS). Balancing of crisp granules and sub fuzzy granules, within non fuzzy information (initial granulation), is rendered in an open-close iteration. Using two criteria, "simplicity of rules "and "adaptive threoshold error level", stability of algorithm is guaranteed. Validation of the proposed method, on the data set of the hydrocyclone is rendered.

0805.3518

Gianluca Caminiti

Francesco Buccafurri and Gianluca Caminiti

Logic programming with social features

49 pages, 0 figures, to appear in Theory and Practice of Logic Programming (TPLP)

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

In everyday life it happens that a person has to reason about what other people think and how they behave, in order to achieve his goals. In other words, an individual may be required to adapt his behaviour by reasoning about the others' mental state. In this paper we focus on a knowledge representation language derived from logic programming which both supports the representation of mental states of individual communities and provides each with the capability of reasoning about others' mental states and acting accordingly. The proposed semantics is shown to be translatable into stable model semantics of logic programs with aggregates.

0805.3747

Anon Plangprasopchok

Anon Plangprasopchok and Kristina Lerman

Constructing Folksonomies from User-specified Relations on Flickr

14 Pages, Submitted to the Workshop on Web Mining and Web Usage Analysis (WebKDD 2008)

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Many social Web sites allow users to publish content and annotate with descriptive metadata. In addition to flat tags, some social Web sites have recently began to allow users to organize their content and metadata hierarchically. The social photosharing site Flickr, for example, allows users to group related photos in sets, and related sets in collections. The social bookmarking site Del.icio.us similarly lets users group related tags into bundles. Although the sites themselves don't impose any constraints on how these hierarchies are used, individuals generally use them to capture relationships between concepts, most commonly the broader/narrower relations. Collective annotation of content with hierarchical relations may lead to an emergent classification system, called a folksonomy. While some researchers have explored using tags as evidence for learning folksonomies, we believe that hierarchical relations described above offer a high-quality source of evidence for this task. We propose a simple approach to aggregate shallow hierarchies created by many distinct Flickr users into a common folksonomy. Our approach uses statistics to determine if a particular relation should be retained or discarded. The relations are then woven together into larger hierarchies. Although we have not carried out a detailed quantitative evaluation of the approach, it looks very promising since it generates very reasonable, non-trivial hierarchies.

0805.3799

Fionn Murtagh

Fionn Murtagh, Adam Ganz and Stewart McKie

The Structure of Narrative: the Case of Film Scripts

28 pages, 7 figures, 21 references

Pattern Recognition, 42 (2), 302-312, 2009

10.1016/j.patcog.2008.05.026

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

We analyze the style and structure of story narrative using the case of film scripts. The practical importance of this is noted, especially the need to have support tools for television movie writing. We use the Casablanca film script, and scripts from six episodes of CSI (Crime Scene Investigation). For analysis of style and structure, we quantify various central perspectives discussed in McKee's book, "Story: Substance, Structure, Style, and the Principles of Screenwriting". Film scripts offer a useful point of departure for exploration of the analysis of more general narratives. Our methodology, using Correspondence Analysis, and hierarchical clustering, is innovative in a range of areas that we discuss. In particular this work is groundbreaking in taking the qualitative analysis of McKee and grounding this analysis in a quantitative and algorithmic framework.

0805.3802

Vitaly Schetinin

L. Jakaite and V. Schetinin

Feature Selection for Bayesian Evaluation of Trauma Death Risk

4 pages, 14th Nordic Baltic Conference on Biomedical Engineering and Medical Physics

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

In the last year more than 70,000 people have been brought to the UK hospitals with serious injuries. Each time a clinician has to urgently take a patient through a screening procedure to make a reliable decision on the trauma treatment. Typically, such procedure comprises around 20 tests; however the condition of a trauma patient remains very difficult to be tested properly. What happens if these tests are ambiguously interpreted, and information about the severity of the injury will come misleading? The mistake in a decision can be fatal: using a mild treatment can put a patient at risk of dying from posttraumatic shock, while using an overtreatment can also cause death. How can we reduce the risk of the death caused by unreliable decisions? It has been shown that probabilistic reasoning, based on the Bayesian methodology of averaging over decision models, allows clinicians to evaluate the uncertainty in decision making. Based on this methodology, in this paper we aim at selecting the most important screening tests, keeping a high performance. We assume that the probabilistic reasoning within the Bayesian methodology allows us to discover new relationships between the screening tests and uncertainty in decisions. In practice, selection of the most informative tests can also reduce the cost of a screening procedure in trauma care centers. In our experiments we use the UK Trauma data to compare the efficiency of the proposed technique in terms of the performance. We also compare the uncertainty in decisions in terms of entropy.

0805.3935

Arnaud Martin

Arnaud Martin (E3I2)

Fusion for Evaluation of Image Classification in Uncertain Environments

Dans Proceeding of the 9th International Conference on Information Fusion - Information Fusion, Florence : Italie (2006)

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

We present in this article a new evaluation method for classification and segmentation of textured images in uncertain environments. In uncertain environments, real classes and boundaries are known with only a partial certainty given by the experts. Most of the time, in many presented papers, only classification or only segmentation are considered and evaluated. Here, we propose to take into account both the classification and segmentation results according to the certainty given by the experts. We present the results of this method on a fusion of classifiers of sonar images for a seabed characterization.

0805.3972

Yoshiharu Maeno

Yoshiharu Maeno, and Yukio Ohsawa

Intuitive visualization of the intelligence for the run-down of terrorist wire-pullers

10 pages, and 2 figures

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

The investigation of the terrorist attack is a time-critical task. The investigators have a limited time window to diagnose the organizational background of the terrorists, to run down and arrest the wire-pullers, and to take an action to prevent or eradicate the terrorist attack. The intuitive interface to visualize the intelligence data set stimulates the investigators' experience and knowledge, and aids them in decision-making for an immediately effective action. This paper presents a computational method to analyze the intelligence data set on the collective actions of the perpetrators of the attack, and to visualize it into the form of a social network diagram which predicts the positions where the wire-pullers conceals themselves.

0805.4560

\^Hamed \"Owladeghaffari

H.Owladeghaffari

Rock mechanics modeling based on soft granulation theory

10.1016/j.ijrmms.2008.09.001

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

This paper describes application of information granulation theory, on the design of rock engineering flowcharts. Firstly, an overall flowchart, based on information granulation theory has been highlighted. Information granulation theory, in crisp (non-fuzzy) or fuzzy format, can take into account engineering experiences (especially in fuzzy shape-incomplete information or superfluous), or engineering judgments, in each step of designing procedure, while the suitable instruments modeling are employed. In this manner and to extension of soft modeling instruments, using three combinations of Self Organizing Map (SOM), Neuro-Fuzzy Inference System (NFIS), and Rough Set Theory (RST) crisp and fuzzy granules, from monitored data sets are obtained. The main underlined core of our algorithms are balancing of crisp(rough or non-fuzzy) granules and sub fuzzy granules, within non fuzzy information (initial granulation) upon the open-close iterations. Using different criteria on balancing best granules (information pockets), are obtained. Validations of our proposed methods, on the data set of in-situ permeability in rock masses in Shivashan dam, Iran have been highlighted.

0806.0526

Pradorn Sureephong

Pradorn Sureephong (LIESP, CAMT), Nopasit Chakpitak (CAMT), Yacine Ouzrout (LIESP), Abdelaziz Bouras (LIESP)

An Ontology-based Knowledge Management System for Industry Clusters

Dans Proceeding of International Conference on Advanced Design and Manufacture - International Conference on Advanced Design and Manufacture (ICADAM 2008), Sanya : Chine (2008)

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Knowledge-based economy forces companies in the nation to group together as a cluster in order to maintain their competitiveness in the world market. The cluster development relies on two key success factors which are knowledge sharing and collaboration between the actors in the cluster. Thus, our study tries to propose knowledge management system to support knowledge management activities within the cluster. To achieve the objectives of this study, ontology takes a very important role in knowledge management process in various ways; such as building reusable and faster knowledge-bases, better way for representing the knowledge explicitly. However, creating and representing ontology create difficulties to organization due to the ambiguity and unstructured of source of knowledge. Therefore, the objectives of this paper are to propose the methodology to create and represent ontology for the organization development by using knowledge engineering approach. The handicraft cluster in Thailand is used as a case study to illustrate our proposed methodology.

0806.1280

Khaled Khalil

Khaled M. Khalil, M. Abdel-Aziz, Taymour T. Nazmy and Abdel-Badeeh M. Salem

The Role of Artificial Intelligence Technologies in Crisis Response

6 pages, 5 figures, 1 table, accepted for MENDEL 2008 14th International Conference on Soft Computing, June 18-20, Brno, Czech Republic

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Crisis response poses many of the most difficult information technology in crisis management. It requires information and communication-intensive efforts, utilized for reducing uncertainty, calculating and comparing costs and benefits, and managing resources in a fashion beyond those regularly available to handle routine problems. In this paper, we explore the benefits of artificial intelligence technologies in crisis response. This paper discusses the role of artificial intelligence technologies; namely, robotics, ontology and semantic web, and multi-agent systems in crisis response.

0806.1640

Arnaud Martin

Arnaud Martin (E3I2), Christophe Osswald (E3I2)

Toward a combination rule to deal with partial conflict and specificity in belief functions theory

International Conference on Information Fusion, Qu\'ebec : Canada (2007)

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

We present and discuss a mixed conjunctive and disjunctive rule, a generalization of conflict repartition rules, and a combination of these two rules. In the belief functions theory one of the major problem is the conflict repartition enlightened by the famous Zadeh's example. To date, many combination rules have been proposed in order to solve a solution to this problem. Moreover, it can be important to consider the specificity of the responses of the experts. Since few year some unification rules are proposed. We have shown in our previous works the interest of the proportional conflict redistribution rule. We propose here a mixed combination rule following the proportional conflict redistribution rule modified by a discounting procedure. This rule generalizes many combination rules.

0806.1797

Arnaud Martin

Arnaud Martin (E3I2), Christophe Osswald (E3I2)

A new generalization of the proportional conflict redistribution rule stable in terms of decision

Advances and Applications of DSmT for Information Fusion, Florentin Smarandache & Jean Dezert (Ed.) (2006) 69-88

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

In this chapter, we present and discuss a new generalized proportional conflict redistribution rule. The Dezert-Smarandache extension of the Demster-Shafer theory has relaunched the studies on the combination rules especially for the management of the conflict. Many combination rules have been proposed in the last few years. We study here different combination rules and compare them in terms of decision on didactic example and on generated data. Indeed, in real applications, we need a reliable decision and it is the final results that matter. This chapter shows that a fine proportional conflict redistribution rule must be preferred for the combination in the belief function theory.

0806.1802

Arnaud Martin

Arnaud Martin (E3I2), Christophe Osswald (E3I2)

Une nouvelle r\`egle de combinaison r\'epartissant le conflit - Applications en imagerie Sonar et classification de cibles Radar

Revue Traitement du Signal 24, 2 (2007) 71-82

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

These last years, there were many studies on the problem of the conflict coming from information combination, especially in evidence theory. We can summarise the solutions for manage the conflict into three different approaches: first, we can try to suppress or reduce the conflict before the combination step, secondly, we can manage the conflict in order to give no influence of the conflict in the combination step, and then take into account the conflict in the decision step, thirdly, we can take into account the conflict in the combination step. The first approach is certainly the better, but not always feasible. It is difficult to say which approach is the best between the second and the third. However, the most important is the produced results in applications. We propose here a new combination rule that distributes the conflict proportionally on the element given this conflict. We compare these different combination rules on real data in Sonar imagery and Radar target classification.

0806.1806

Guido Tack

Christian Schulte and Guido Tack

Perfect Derived Propagators

17 pages, 2 tables

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

When implementing a propagator for a constraint, one must decide about variants: When implementing min, should one also implement max? Should one implement linear equations both with and without coefficients? Constraint variants are ubiquitous: implementing them requires considerable (if not prohibitive) effort and decreases maintainability, but will deliver better performance. This paper shows how to use variable views, previously introduced for an implementation architecture, to derive perfect propagator variants. A model for views and derived propagators is introduced. Derived propagators are proved to be indeed perfect in that they inherit essential properties such as correctness and domain and bounds consistency. Techniques for systematically deriving propagators such as transformation, generalization, specialization, and channeling are developed for several variable domains. We evaluate the massive impact of derived propagators. Without derived propagators, Gecode would require 140000 rather than 40000 lines of code for propagators.

0806.2140

Joseph Y. Halpern

Joseph Y. Halpern

Defaults and Normality in Causal Structures

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

A serious defect with the Halpern-Pearl (HP) definition of causality is repaired by combining a theory of causality with a theory of defaults. In addition, it is shown that (despite a claim to the contrary) a cause according to the HP condition need not be a single conjunct. A definition of causality motivated by Wright's NESS test is shown to always hold for a single conjunct. Moreover, conditions that hold for all the examples considered by HP are given that guarantee that causality according to (this version) of the NESS test is equivalent to the HP definition.

0806.4511

Konstantin Wishnevsky Mr.

Konstantin P. Wishnevsky

The model of quantum evolution

This paper has been withdrawn

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

This paper has been withdrawn by the author due to extremely unscientific errors.

0807.0627

Arnaud Martin

Arnaud Martin (E3I2)

Belief decision support and reject for textured images characterization

International Conference on Information Fusion, Lens : France (2008)

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

The textured images' classification assumes to consider the images in terms of area with the same texture. In uncertain environment, it could be better to take an imprecise decision or to reject the area corresponding to an unlearning class. Moreover, on the areas that are the classification units, we can have more than one texture. These considerations allows us to develop a belief decision model permitting to reject an area as unlearning and to decide on unions and intersections of learning classes. The proposed approach finds all its justification in an application of seabed characterization from sonar images, which contributes to an illustration.

0807.0908

Fionn Murtagh

Fionn Murtagh

The Correspondence Analysis Platform for Uncovering Deep Structure in Data and Information

Sixth Annual Boole Lecture in Informatics, Boole Centre for Research in Informatics, Cork, Ireland, 29 April 2008. 28 pp., 17 figures. To appear, Computer Journal. This version: 3 typos corrected

Computer Journal, 53 (3), 304-315, 2010

10.1093/comjnl/bxn045

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

We study two aspects of information semantics: (i) the collection of all relationships, (ii) tracking and spotting anomaly and change. The first is implemented by endowing all relevant information spaces with a Euclidean metric in a common projected space. The second is modelled by an induced ultrametric. A very general way to achieve a Euclidean embedding of different information spaces based on cross-tabulation counts (and from other input data formats) is provided by Correspondence Analysis. From there, the induced ultrametric that we are particularly interested in takes a sequential - e.g. temporal - ordering of the data into account. We employ such a perspective to look at narrative, "the flow of thought and the flow of language" (Chafe). In application to policy decision making, we show how we can focus analysis in a small number of dimensions.

0807.1906

Florentin Smarandache

Florentin Smarandache

Extension of Inagaki General Weighted Operators and A New Fusion Rule Class of Proportional Redistribution of Intersection Masses

6 pages; SWIFT 2008 - Skovde Workshop on Information Fusion Topics, Sweden;

International Journal of Artificial Intelligence, Vol. 3, No. A09, 79-85, 2009

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

In this paper we extend Inagaki Weighted Operators fusion rule (WO) in information fusion by doing redistribution of not only the conflicting mass, but also of masses of non-empty intersections, that we call Double Weighted Operators (DWO). Then we propose a new fusion rule Class of Proportional Redistribution of Intersection Masses (CPRIM), which generates many interesting particular fusion rules in information fusion. Both formulas are presented for any number of sources of information. An application and comparison with other fusion rules are given in the last section.

0807.3483

Arnaud Martin

Arnaud Martin (E3I2)

Implementing general belief function framework with a practical codification for low complexity

Advances and Applications of DSmT for Information Fusion, Florentin Smarandache & Jean Dezert (Ed.) (2008) Pnd

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

In this chapter, we propose a new practical codification of the elements of the Venn diagram in order to easily manipulate the focal elements. In order to reduce the complexity, the eventual constraints must be integrated in the codification at the beginning. Hence, we only consider a reduced hyper power set $D_r^\Theta$ that can be $2^\Theta$ or $D^\Theta$. We describe all the steps of a general belief function framework. The step of decision is particularly studied, indeed, when we can decide on intersections of the singletons of the discernment space no actual decision functions are easily to use. Hence, two approaches are proposed, an extension of previous one and an approach based on the specificity of the elements on which to decide. The principal goal of this chapter is to provide practical codes of a general belief function framework for the researchers and users needing the belief function theory.

0807.3669

Jean Dezert

Jean Dezert (ONERA), Florentin Smarandache

A new probabilistic transformation of belief mass assignment

Fusion 2008 International Conference on Information Fusion, Cologne : Allemagne (2008)

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

In this paper, we propose in Dezert-Smarandache Theory (DSmT) framework, a new probabilistic transformation, called DSmP, in order to build a subjective probability measure from any basic belief assignment defined on any model of the frame of discernment. Several examples are given to show how the DSmP transformation works and we compare it to main existing transformations proposed in the literature so far. We show the advantages of DSmP over classical transformations in term of Probabilistic Information Content (PIC). The direct extension of this transformation for dealing with qualitative belief assignments is also presented.

0807.4417

Daniel Sonntag

Daniel Sonntag

On Introspection, Metacognitive Control and Augmented Data Mining Live Cycles

10 pages, 3 figures

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

We discuss metacognitive modelling as an enhancement to cognitive modelling and computing. Metacognitive control mechanisms should enable AI systems to self-reflect, reason about their actions, and to adapt to new situations. In this respect, we propose implementation details of a knowledge taxonomy and an augmented data mining life cycle which supports a live integration of obtained models.

0807.4680

Sergio Miguel Tome

Sergio Miguel

Hacia una teoria de unificacion para los comportamientos cognitivos

63 pages, 4 figures, Spanish, mistakes erased

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Each cognitive science tries to understand a set of cognitive behaviors. The structuring of knowledge of this nature's aspect is far from what it can be expected about a science. Until now universal standard consistently describing the set of cognitive behaviors has not been found, and there are many questions about the cognitive behaviors for which only there are opinions of members of the scientific community. This article has three proposals. The first proposal is to raise to the scientific community the necessity of unified the cognitive behaviors. The second proposal is claim the application of the Newton's reasoning rules about nature of his book, Philosophiae Naturalis Principia Mathematica, to the cognitive behaviors. The third is to propose a scientific theory, currently developing, that follows the rules established by Newton to make sense of nature, and could be the theory to explain all the cognitive behaviors.

0808.1125

Omid David-Tabibi

Omid David-Tabibi and Nathan S. Netanyahu

Verified Null-Move Pruning

9 pages

ICGA Journal, International Computer Games Association, Vol. 25, No. 3, pp. 153--161, September 2002

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

In this article we review standard null-move pruning and introduce our extended version of it, which we call verified null-move pruning. In verified null-move pruning, whenever the shallow null-move search indicates a fail-high, instead of cutting off the search from the current node, the search is continued with reduced depth. Our experiments with verified null-move pruning show that on average, it constructs a smaller search tree with greater tactical strength in comparison to standard null-move pruning. Moreover, unlike standard null-move pruning, which fails badly in zugzwang positions, verified null-move pruning manages to detect most zugzwangs and in such cases conducts a re-search to obtain the correct result. In addition, verified null-move pruning is very easy to implement, and any standard null-move pruning program can use verified null-move pruning by modifying only a few lines of code.

0808.3109

Florentin Smarandache

Florentin Smarandache, V. Christianto

n-ary Fuzzy Logic and Neutrosophic Logic Operators

15 pages, 2 fuzzy and neutrosophic value tables, many diagrams

Studies in Logic, Grammar and Rethoric [Belarus], 17 (30), pp. 1-16, 2009.

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

We extend Knuth's 16 Boolean binary logic operators to fuzzy logic and neutrosophic logic binary operators. Then we generalize them to n-ary fuzzy logic and neutrosophic logic operators using the smarandache codification of the Venn diagram and a defined vector neutrosophic law. In such way, new operators in neutrosophic logic/set/probability are built.

0809.0271

Martin Josef Geiger

Martin Josef Geiger

Randomised Variable Neighbourhood Search for Multi Objective Optimisation

Proceedings of the 4th EU/ME Workshop: Design and Evaluation of Advanced Hybrid Meta-Heuristics, November 4--5, Nottingham, United Kingdom, pp. 34-42

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Various local search approaches have recently been applied to machine scheduling problems under multiple objectives. Their foremost consideration is the identification of the set of Pareto optimal alternatives. An important aspect of successfully solving these problems lies in the definition of an appropriate neighbourhood structure. Unclear in this context remains, how interdependencies within the fitness landscape affect the resolution of the problem. The paper presents a study of neighbourhood search operators for multiple objective flow shop scheduling. Experiments have been carried out with twelve different combinations of criteria. To derive exact conclusions, small problem instances, for which the optimal solutions are known, have been chosen. Statistical tests show that no single neighbourhood operator is able to equally identify all Pareto optimal alternatives. Significant improvements however have been obtained by hybridising the solution algorithm using a randomised variable neighbourhood search technique.

0809.0406

Martin Josef Geiger

Martin Josef Geiger

Foundations of the Pareto Iterated Local Search Metaheuristic

Proceedings of the 18th International Conference on Multiple Criteria Decision Making, Chania, Greece, June 19-23, 2006

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

The paper describes the proposition and application of a local search metaheuristic for multi-objective optimization problems. It is based on two main principles of heuristic search, intensification through variable neighborhoods, and diversification through perturbations and successive iterations in favorable regions of the search space. The concept is successfully tested on permutation flow shop scheduling problems under multiple objectives. While the obtained results are encouraging in terms of their quality, another positive attribute of the approach is its' simplicity as it does require the setting of only very few parameters. The implementation of the Pareto Iterated Local Search metaheuristic is based on the MOOPPS computer system of local search heuristics for multi-objective scheduling which has been awarded the European Academic Software Award 2002 in Ronneby, Sweden (http://www.easa-award.net/, http://www.bth.se/llab/easa_2002.nsf)

0809.0410

Martin Josef Geiger

Martin Josef Geiger

A Computational Study of Genetic Crossover Operators for Multi-Objective Vehicle Routing Problem with Soft Time Windows

Habenicht, W. et al. (eds.): Multi-Criteria- und Fuzzy Systeme in Theorie und Praxis-Loesungsansaetze fuer Entscheidungsprobleme mit komplexen Zielsystemen, 2003, ISBN 3-8244-7864-1, pp. 191-207

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

The article describes an investigation of the effectiveness of genetic algorithms for multi-objective combinatorial optimization (MOCO) by presenting an application for the vehicle routing problem with soft time windows. The work is motivated by the question, if and how the problem structure influences the effectiveness of different configurations of the genetic algorithm. Computational results are presented for different classes of vehicle routing problems, varying in their coverage with time windows, time window size, distribution and number of customers. The results are compared with a simple, but effective local search approach for multi-objective combinatorial optimization problems.

0809.0416

Martin Josef Geiger

Martin Josef Geiger

Genetic Algorithms for multiple objective vehicle routing

Proceedings of the Metaheuristics International Conference MIC'2001, Porto, Portugal, pp. 349-353

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

The talk describes a general approach of a genetic algorithm for multiple objective optimization problems. A particular dominance relation between the individuals of the population is used to define a fitness operator, enabling the genetic algorithm to adress even problems with efficient, but convex-dominated alternatives. The algorithm is implemented in a multilingual computer program, solving vehicle routing problems with time windows under multiple objectives. The graphical user interface of the program shows the progress of the genetic algorithm and the main parameters of the approach can be easily modified. In addition to that, the program provides powerful decision support to the decision maker. The software has proved it's excellence at the finals of the European Academic Software Award EASA, held at the Keble college/ University of Oxford/ Great Britain.

0809.0610

Martin Josef Geiger

Martin Josef Geiger, Wolf Wenger

A framework for the interactive resolution of multi-objective vehicle routing problems

Proceedings of the 7th EU/ME Workshop: Adaptive, Self-Adaptive, and Multi-Level Metaheuristics, Malaga, Spain, November 16-17, 2006

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

The article presents a framework for the resolution of rich vehicle routing problems which are difficult to address with standard optimization techniques. We use local search on the basis on variable neighborhood search for the construction of the solutions, but embed the techniques in a flexible framework that allows the consideration of complex side constraints of the problem such as time windows, multiple depots, heterogeneous fleets, and, in particular, multiple optimization criteria. In order to identify a compromise alternative that meets the requirements of the decision maker, an interactive procedure is integrated in the resolution of the problem, allowing the modification of the preference information articulated by the decision maker. The framework is prototypically implemented in a computer system. First results of test runs on multiple depot vehicle routing problems with time windows are reported.

0809.0662

Martin Josef Geiger

Martin Josef Geiger, Sanja Petrovic

Improving Local Search for Fuzzy Scheduling Problems

Proceedings of the Post Graduate Research Conference in Electronics, Photonics, Communications & Networks and Computing Science PREP 2004, University of Hertfordshire, Great Britain, pp. 146-147

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

The integration of fuzzy set theory and fuzzy logic into scheduling is a rather new aspect with growing importance for manufacturing applications, resulting in various unsolved aspects. In the current paper, we investigate an improved local search technique for fuzzy scheduling problems with fitness plateaus, using a multi criteria formulation of the problem. We especially address the problem of changing job priorities over time as studied at the Sherwood Press Ltd, a Nottingham based printing company, who is a collaborator on the project.

0809.0755

Martin Josef Geiger

Martin Josef Geiger

Bin Packing Under Multiple Objectives - a Heuristic Approximation Approach

The Fourth International Conference on Evolutionary Multi-Criterion Optimization: Late Breaking Papers, Matsushima, Japan, March 2007, pp. 53-56

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

The article proposes a heuristic approximation approach to the bin packing problem under multiple objectives. In addition to the traditional objective of minimizing the number of bins, the heterogeneousness of the elements in each bin is minimized, leading to a biobjective formulation of the problem with a tradeoff between the number of bins and their heterogeneousness. An extension of the Best-Fit approximation algorithm is presented to solve the problem. Experimental investigations have been carried out on benchmark instances of different size, ranging from 100 to 1000 items. Encouraging results have been obtained, showing the applicability of the heuristic approach to the described problem.

0809.0757

Martin Josef Geiger

Martin Josef Geiger

An application of the Threshold Accepting metaheuristic for curriculum based course timetabling

Proceedings of the 7th International Conference on the Practice and Theory of Automated Timetabling PATAT 2008, August 19-22, Montreal, Canada

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

The article presents a local search approach for the solution of timetabling problems in general, with a particular implementation for competition track 3 of the International Timetabling Competition 2007 (ITC 2007). The heuristic search procedure is based on Threshold Accepting to overcome local optima. A stochastic neighborhood is proposed and implemented, randomly removing and reassigning events from the current solution. The overall concept has been incrementally obtained from a series of experiments, which we describe in each (sub)section of the paper. In result, we successfully derived a potential candidate solution approach for the finals of track 3 of the ITC 2007.

0809.1077

Martin Josef Geiger

Martin Josef Geiger, Wolf Wenger

Variable Neighborhood Search for the University Lecturer-Student Assignment Problem

Proceedings of the 18th Mini Euro Conference on Variable Neighborhood Search, November 23-25, 2005, Puerto de La Cruz, Tenerife, Spain, ISBN 84-689-5679-1

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

The paper presents a study of local search heuristics in general and variable neighborhood search in particular for the resolution of an assignment problem studied in the practical work of universities. Here, students have to be assigned to scientific topics which are proposed and supported by members of staff. The problem involves the optimization under given preferences of students which may be expressed when applying for certain topics. It is possible to observe that variable neighborhood search leads to superior results for the tested problem instances. One instance is taken from an actual case, while others have been generated based on the real world data to support the analysis with a deeper analysis. An extension of the problem has been formulated by integrating a second objective function that simultaneously balances the workload of the members of staff while maximizing utility of the students. The algorithmic approach has been prototypically implemented in a computer system. One important aspect in this context is the application of the research work to problems of other scientific institutions, and therefore the provision of decision support functionalities.

0809.3204

Matti J\"arvisalo

Matti J\"arvisalo and Emilia Oikarinen

Extended ASP tableaux and rule redundancy in normal logic programs

27 pages, 5 figures, 1 table

Theory and Practice of Logic Programming, 8(5-6):691-716, 2008

10.1017/S1471068408003578

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

We introduce an extended tableau calculus for answer set programming (ASP). The proof system is based on the ASP tableaux defined in [Gebser&Schaub, ICLP 2006], with an added extension rule. We investigate the power of Extended ASP Tableaux both theoretically and empirically. We study the relationship of Extended ASP Tableaux with the Extended Resolution proof system defined by Tseitin for sets of clauses, and separate Extended ASP Tableaux from ASP Tableaux by giving a polynomial-length proof for a family of normal logic programs P_n for which ASP Tableaux has exponential-length minimal proofs with respect to n. Additionally, Extended ASP Tableaux imply interesting insight into the effect of program simplification on the lengths of proofs in ASP. Closely related to Extended ASP Tableaux, we empirically investigate the effect of redundant rules on the efficiency of ASP solving. To appear in Theory and Practice of Logic Programming (TPLP).

0809.4582

Emilia Oikarinen

Emilia Oikarinen, Tomi Janhunen

Achieving compositionality of the stable model semantics for Smodels programs

44 pages, 2 tables

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

In this paper, a Gaifman-Shapiro-style module architecture is tailored to the case of Smodels programs under the stable model semantics. The composition of Smodels program modules is suitably limited by module conditions which ensure the compatibility of the module system with stable models. Hence the semantics of an entire Smodels program depends directly on stable models assigned to its modules. This result is formalized as a module theorem which truly strengthens Lifschitz and Turner's splitting-set theorem for the class of Smodels programs. To streamline generalizations in the future, the module theorem is first proved for normal programs and then extended to cover Smodels programs using a translation from the latter class of programs to the former class. Moreover, the respective notion of module-level equivalence, namely modular equivalence, is shown to be a proper congruence relation: it is preserved under substitutions of modules that are modularly equivalent. Principles for program decomposition are also addressed. The strongly connected components of the respective dependency graph can be exploited in order to extract a module structure when there is no explicit a priori knowledge about the modules of a program. The paper includes a practical demonstration of tools that have been developed for automated (de)composition of Smodels programs. To appear in Theory and Practice of Logic Programming.

0810.0139

Wilson Wong

Wilson Wong, Wei Liu, Mohammed Bennamoun

Determining the Unithood of Word Sequences using a Probabilistic Approach

More information is available at http://explorer.csse.uwa.edu.au/reference/

3rd International Joint Conference on Natural Language Processing (IJCNLP), 2008, pages 103-110

cs.AI

http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Most research related to unithood were conducted as part of a larger effort for the determination of termhood. Consequently, novelties are rare in this small sub-field of term extraction. In addition, existing work were mostly empirically motivated and derived. We propose a new probabilistically-derived measure, independent of any influences of termhood, that provides dedicated measures to gather linguistic evidence from parsed text and statistical evidence from Google search engine for the measurement of unithood. Our comparative study using 1,825 test cases against an existing empirically-derived function revealed an improvement in terms of precision, recall and accuracy.

0810.0156

Wilson Wong

Wilson Wong, Wei Liu, Mohammed Bennamoun

Determining the Unithood of Word Sequences using Mutual Information and Independence Measure

More information is available at http://explorer.csse.uwa.edu.au/reference/

10th Conference of the Pacific Association for Computational Linguistics (PACLING), 2007, pages 246-254

CSSE-WWONG-13

cs.AI

http://creativecommons.org/licenses/by/3.0/

Most works related to unithood were conducted as part of a larger effort for the determination of termhood. Consequently, the number of independent research that study the notion of unithood and produce dedicated techniques for measuring unithood is extremely small. We propose a new approach, independent of any influences of termhood, that provides dedicated measures to gather linguistic evidence from parsed text and statistical evidence from Google search engine for the measurement of unithood. Our evaluations revealed a precision and recall of 98.68% and 91.82% respectively with an accuracy at 95.42% in measuring the unithood of 1005 test cases.