We present an approximation method that solves a class of Decentralized hybrid Markov Decision Processes (DEC-HMDPs). These DEC-HMDPs have both discrete and continuous state variab...
Decentralized Markov Decision Processes (DEC-MDPs) are a popular model of agent-coordination problems in domains with uncertainty and time constraints but very difficult to solve...
There has been substantial progress with formal models for sequential decision making by individual agents using the Markov decision process (MDP). However, similar treatment of m...
Raphen Becker, Shlomo Zilberstein, Victor R. Lesse...
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. ...
We give an optimal dynamic programming algorithm to solve a class of finite-horizon decentralized Markov decision processes (MDPs). We consider problems with a broadcast informati...