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README.md

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+---
+tags:
+- Pixelcopter-PLE-v0
+- dqn
+- deep-q-learning
+- reinforcement-learning
+- custom-implementation
+model-index:
+- name: Reinforce-Pixelcopter-PLE-v4
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: Pixelcopter-PLE-v0
+      type: Pixelcopter-PLE-v0
+    metrics:
+    - type: mean_reward
+      value: 25.20 +/- 19.11
+      name: mean_reward
+      verified: false
+---
+
+# **DQN** Agent playing **Pixelcopter-PLE-v0**
+This is a trained model of a **Deep Q-Network (DQN)** agent playing **Pixelcopter-PLE-v0**.

dqn_model.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e6520b67702b3abd4bd12ddfaac096ad74be6080ba1461bbbb17c5090d6f8340
+size 40152

hyperparameters.json

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+{"h_size": 64, "gamma": 0.99, "lr": 0.001, "batch_size": 64, "buffer_size": 100000, "epsilon_start": 1.0, "epsilon_end": 0.01, "epsilon_decay": 10000, "target_update": 1000, "n_episodes": 25000, "max_t": 5000, "n_evaluation_episodes": 10, "env_id": "Pixelcopter-PLE-v0"}

results.json

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+{"env_id": "Pixelcopter-PLE-v0", "mean_reward": 25.2, "n_evaluation_episodes": 10, "eval_datetime": "2025-02-17T05:59:25.812447"}