Reinforcement Learning Repository at MSU

Topics: Function Approximation

Reinforcement learning methods operate by inferring the value function from online experience. However, in most interesting applications, the state space is too large to enumerate the value function. Some function approximator must be used to compactly represent the value function. Many approaches have been tried, but the most popular methods are neural nets, clustering, nearest-neighbor methods, and CMAC.