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--- |
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tags: |
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- MountainCar-v0 |
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- deep-reinforcement-learning |
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- reinforcement-learning |
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model-index: |
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- name: DQN |
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results: |
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- task: |
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type: reinforcement-learning |
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name: reinforcement-learning |
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dataset: |
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name: MountainCar-v0 |
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type: MountainCar-v0 |
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metrics: |
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- type: mean_reward |
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value: '-120.10 +/- 19.30' |
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name: mean_reward |
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verified: false |
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license: afl-3.0 |
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--- |
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|
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# **DQN** Agent playing **MountainCar-v0** |
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This is a trained model of a **DQN** agent playing **MountainCar-v0**. |
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We train a three-layer MLP as the Q-network. |
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We store the transitions in a replay buffer. |
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After the network converges, we stop training and validate its performance in |
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comparison to a random baseline. |
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Parameters: |
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```python |
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hidden_size = 64 |
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gamma = 0.99 |
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epsilon_decay = 0.999 |
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buffer_size = 10000 |
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batch_size = 64 |
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episodes = 10000 |
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``` |
