iamhectorotero/rlai-exercises
Exercise Solutions for Reinforcement Learning: An Introduction [2nd Edition]
Implements solutions across foundational RL concepts including multi-armed bandits, Markov decision processes, dynamic programming, and temporal difference learning. Solutions combine mathematical derivations with Python implementations of core algorithms like Q-learning and policy gradient methods. Designed as a companion resource to validate understanding against the textbook's theoretical frameworks and exercises.
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