Generalization in Reinforcement Learning: Successful Examples Using Sparse Coarse Coding


On large problems, reinforcement learning systems must use parameterized function approximators such as neural networks in order to generalize between similar situations and actions. In these cases there are no strong theoretical results on the accuracy of convergence, and computational results have been mixed. In particular, Boyan and Moore reported at… (More)


6 Figures and Tables


Citations per Year

911 Citations

Semantic Scholar estimates that this publication has 911 citations based on the available data.

See our FAQ for additional information.