Journal of Arti cial Intelligence Research 4 (1996) 237-285 Submitted 9/95; published 5/96 Reinforcement Learning: A Survey Leslie Pack Kaelbling lpk@cs.brown.edu Michael L. Littman mlittman@cs.brown.edu Computer Science Department, Box 1910, Brown University Providence, RI 02912-1910 USA Andrew W. Moore awm@cs.cmu.edu Smith Hall 221, Carnegie Mellon University, 5000 Forbes Avenue Pittsburgh, PA 15213 USA Abstract This paper surveys the eld of reinforcement learning from a computer-science per- spective. It is written to be accessible to researchers familiar with machine learning. Both the historical basis of the eld and a broad selection of current work 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 di ers considerably in the details and in the use of the word \reinforcement." The paper dis
