Reinforcement Learning Repository at MSU

Topics: Temporal Difference Learning

Temporal difference (TD) methods is a general framework for solving sequential prediction and control problems, whereby an agent learns by comparing temporally successive predictions. A key strength of TD methods is that the agent can learn before seeing the final outcome. Q-learning is one of the most popular TD methods.