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Reinforcement Learning with Gymnasium in Python
Fouad Trad
Machine Learning Engineer
Chapter 1
Introduction to reinforcement learning
Fundamentals of RL
RL framework
Gymnasium
Chapter 2
Model-based learning
Markove Decision Process
Policies, value functions
Policy iteration, value iteration
Chapter 3
Model-Free Learning
Monte Carlo methods
Temporal difference learning
SARSA
Q-learning
Chapter 4
Advanced strategies in model-free RL
Expected SARSA
Double Q-learning
Exploration-exploitation
Multi-armed bandits
Next steps
Dive into advanced RL topics
Deep RL
Exploring more complex environments
Creating your own environments
Congratulations!
Reinforcement Learning with Gymnasium in Python
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