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Welcome back to this series on reinforcement learning! Over the next couple of videos, we're going to be building and playing our very first game with reinforcement learning in code!

We're going to use the knowledge we gained last time about Q-learning to teach a reinforcement learning agent how to play a game called Frozen Lake. We'll be using Python and OpenAI's Gym toolkit to develop our algorithm.

Sources:
Reinforcement Learning: An Introduction, Second Edition by Richard S. Sutton and Andrew G. Bartow
http://incompleteideas.net/book/RLbook2020.pdf

Playing Atari with Deep Reinforcement Learning by Deep Mind Technologies
https://www.cs.toronto.edu/~vmnih/docs/dqn.pdf

Thomas Simonini's Frozen Lake Q-learning implementation
https://github.com/simoninithomas/Deep_reinforcement_learning_Course/tree/master/Q%20learning/FrozenLake

OpenAI Gym:
https://gym.openai.com/docs/

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