Reinforcement Learning: A Survey Export

@article{citeulike:4578, abstract = {This paper surveys the field of reinforcement learning from a computer-science perspective. It is written to be accessible to researchers familiar with machine learning. Both the historical basis of the field and a broad selection of currentwork are summarized. Reinforcement learning is the problem faced by an agent that learns behavior through trial-and-error interactions with a dynamic environment. The work described here has a resemblance to work in psychology, but differs considerably in...}, author = {Kaelbling, Leslie P. and Littman, Michael L. and Moore, Andrew P.}, citeulike-article-id = {4578}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.44.2707}, journal = {Journal of Artificial Intelligence Research}, keywords = {computer\_science, learning}, pages = {237--285}, posted-at = {2008-06-09 15:05:17}, priority = {2}, title = {Reinforcement Learning: A Survey}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.44.2707}, volume = {4}, year = {1996} }

TY - JOUR ID - citeulike:4578 L3 - citeulike-article-id:4578 N2 - This paper surveys the field of reinforcement learning from a computer-science perspective. It is written to be accessible to researchers familiar with machine learning. Both the historical basis of the field and a broad selection of currentwork are summarized. Reinforcement learning is the problem faced by an agent that learns behavior through trial-and-error interactions with a dynamic environment. The work described here has a resemblance to work in psychology, but differs considerably in... JF - Journal of Artificial Intelligence Research EP - 285 TI - Reinforcement Learning: A Survey VL - 4 SP - 237 KW - computer_science KW - learning AU - Kaelbling, Leslie AU - Littman, Michael AU - Moore, Andrew PY - 1996/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.44.2707 ER -