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  # **Q-Learning** Agent playing **FrozenLake-v1**
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  This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
 
 
 
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  ## Usage
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  ```python
 
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  # **Q-Learning** Agent playing **FrozenLake-v1**
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  This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
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+ Compared to the 4x4 training model, I increased max_steps to increase likelyhood of finding the goal during exploration. That still did not give a good solution.
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+ Then I decreased decay rate to allow for more exploration and increased learning rate. But mostly it was the lower decay rate that improved the result.
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  ## Usage
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  ```python