Decentralized MDPs provide a powerful formal framework for planning in multi-agent systems, but the complexity of the model limits its usefulness. We study in this paper a class o...
Raphen Becker, Shlomo Zilberstein, Victor R. Lesse...
The allocation of scarce spectral resources to support as many user applications as possible while maintaining reasonable quality of service is a fundamental problem in wireless c...
Zygmunt J. Haas, Joseph Y. Halpern, Erran L. Li, S...
Finite-state controllers represent an effective action selection mechanisms widely used in domains such as video-games and mobile robotics. In contrast to the policies obtained fr...
We examine the problem of Transfer in Reinforcement Learning and present a method to utilize knowledge acquired in one Markov Decision Process (MDP) to bootstrap learning in a mor...
ontingent abstraction for robust robot control Joelle Pineau, Geoff Gordon and Sebastian Thrun School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 This pape...
Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun