AI Glossary
A type of machine learning in which an agent learns by trial and error, taking actions and receiving rewards or penalties.
Reinforcement learning powered AlphaGo’s victory at Go, robot control and game-playing agents. In language models it is used for preference tuning and, increasingly, to train reasoning on problems with checkable answers such as math and code.
The hardest parts are designing rewards that capture what you really want and exploring efficiently.
The textbooks and essays that shaped how researchers think about artificial intelligence, from search and logic to deep learning and reinforcement learning.
thelatentdaily.com Editorial Team3 min read
DeepMind's deep Q-network learned dozens of Atari games from raw screen pixels and scores alone. How Q-learning, experience replay and target networks made it work.
thelatentdaily.com Editorial Team3 min read
Proximal Policy Optimization made policy-gradient training simpler and more stable by limiting how far each update can move. How it works and why it is everywhere.
thelatentdaily.com Editorial Team3 min read