128 search results - page 24 / 26 » Hierarchically Optimal Average Reward Reinforcement Learning |
PKDD
2010
Springer
13 years 5 months ago
2010
Springer
Partially observable Markov decision processes (POMDPs) are widely used for planning under uncertainty. In many applications, the huge size of the POMDP state space makes straightf...
ICML
1999
IEEE
14 years 8 months ago
1999
IEEE
Excerpted from: Boyan, Justin. Learning Evaluation Functions for Global Optimization. Ph.D. thesis, Carnegie Mellon University, August 1998. (Available as Technical Report CMU-CS-...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
Inference in Markov Decision Processes has recently received interest as a means to infer goals of an observed action, policy recognition, and also as a tool to compute policies. ...
ICML
1996
IEEE
14 years 8 months ago
1996
IEEE
Some of the most successful recent applications of reinforcement learning have used neural networks and the TD algorithm to learn evaluation functions. In this paper, we examine t...
RECSYS
2009
ACM
14 years 2 months ago
2009
ACM
Previous work on using external aggregate rating information showed that this information can be incorporated in several different types of recommender systems and improves their...