Reinforcement Learning: An Introduction

Overview

The definitive textbook on reinforcement learning by Sutton & Barto — the foundational framework behind AI agents, game-playing AIs, and autonomous decision-making systems.

Full Description

Richard Sutton and Andrew Barto's 'Reinforcement Learning: An Introduction' is the bible of RL — the field that teaches agents to make sequences of decisions by trial and error. The book covers Markov Decision Processes, dynamic programming, Monte Carlo methods, temporal-difference learning, Q-learning, policy gradient methods, and deep RL. It is the theoretical foundation behind AlphaGo, ChatGPT's RLHF training, autonomous vehicle decision-making, and modern AI agent frameworks. Available free online in full.

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