Chapter 21: Reinforcement Learning

Temporal-Difference Learning and Bellman Equations intermediate

"TD methods are the most central and novel idea in reinforcement learning." -- Sutton and Barto (2018)

"TD methods are the most central and novel idea in reinforcement learning." -- Sutton and Barto (2018)

Register to Read

Sign up for a free account to access all 112 primer topics.

Create Free Account

Already have an account? Sign in

Chapter

21 Reinforcement Learning

More Topics

Distributional RL and Tail-Aware Action Selection Markov Decision Processes and Partial Observability Policy Gradient Theorem and Actor-Critic Architectures Reward Shaping and Expected Utility Theory