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Reinforcement learning agent for the OpenAI frozen lake game.

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frozen-lake

This python program implements a reinforcement learning agent for the frozen lake game.

Usage

py frozen-lake.py <environment> <algorithm> <number_of_training_episodes>

Class can be:

  • -s for Sarsa
  • -q for Qlearning

Environment can be:

  • -s for stochastic environment
  • -d for deterministic environment

Example

py frozen-lake.py -d -q 80000

Using deterministic environment.
Using Qlearning algorithm.
Training for  80000  episodes...
Environment has 64 states and 4 actions.
Training done!!!

========================
 Evaluation Episode
========================


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========================
 Success:  goal reached!
========================

Author

Giorgos Argyrides (g.aryrides@outlook.com)

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Reinforcement learning agent for the OpenAI frozen lake game.

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