1998
Sutton RL textbook published
Richard Sutton and Andrew Barto published reinforcement learningTraining agents by reward and penalty signals — used in games, robotics, and recommendation systems.: An Introduction in 1998 — the foundational textbook for RL theory and practice.
What it was for
Sutton's temporal-difference learning and policy-gradient frameworks became the vocabulary for game-playing agents, roboticsMachines that sense, plan, and act in the physical world — from factory arms to Mars rovers., and later DeepMind's AlphaGo. The book's second edition in 2018 updated decades of RL progress.
People
- Rich Sutton — author
Why it's here
Sutton's textbook codified reinforcement learningTraining agents by reward and penalty signals — used in games, robotics, and recommendation systems. as a teachable discipline.
Why it mattered
It trained researchers who built modern game-playing and roboticsMachines that sense, plan, and act in the physical world — from factory arms to Mars rovers. AI.
What it solved
RL ideas were scattered across papers without a unified pedagogical framework.
Media
ImageRichard S. SuttonXuthoria, CC BY-SA 4.0, via Wikimedia Commons
Related
- Demis Hassabis's AlphaGo defeats Lee Sedol 4–1March 15, 2016