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19981990s
Reinforcement Learning Formalization
The definitive mathematical framework for autonomous decision-making.
Why It Was Important
Richard Sutton and Andrew Barto published the textbook 'Reinforcement Learning: An Introduction', consolidating dynamic programming, Monte Carlo methods, and temporal-difference learning into a cohesive framework. This book remains the absolute foundation for anyone entering the field of RL.
Who Invented It
Richard Sutton & Andrew Barto
Academics who unified the disparate threads of trial-and-error learning.
Applications
- Autonomous Agents
- Robotics
- AI Alignment
Key Papers
- Reinforcement Learning: An Introduction
Richard S. Sutton, Andrew G. Barto · MIT Press · 1998
Videos
Reinforcement Learning - Computerphile
Computerphile
Reinforcement Learning from Human Feedback (RLHF) Explained
IBM Technology