Decentralized Markov decision processes are frequently used to model cooperative multi-agent systems. In this paper, we identify a subclass of general DEC-MDPs that features regul...
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...
This paper models and analyzes serial production lines with specialists at each station and a single, cross-trained floating worker who can work at any station. We formulate Marko...
Linn I. Sennott, Mark P. Van Oyen, Seyed M. R. Ira...
Probabilistic planning problems are typically modeled as a Markov Decision Process (MDP). MDPs, while an otherwise expressive model, allow only for sequential, non-durative action...
The Partially Observable Markov Decision Process has long been recognized as a rich framework for real-world planning and control problems, especially in robotics. However exact s...
Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun