POMDP information page

A POMDP is a partially observable Markov decision process. It is a model, originating in the operations research (OR) literature, for describing planning tasks in which the decision maker does not have complete information as to its current state. The POMDP model provides a convenient way of reasoning about tradeoffs between actions to gain reward and actions to gain information.

Michael Littman, Tony Cassandra, and Leslie Kaelbling have been studying this model from an artificial intelligence (AI) perspective. This page provides pointers to their work and also other relevant work in this area. I highly recommend Tony's current (circa Feb 2004) pomdp.org pages.


For more information, contact Michael Littman: mlittman@cs.rutgers.edu. Last update: Mon Feb 9 22:11:10 EST 2004.