The problem of deriving joint policies for a group of agents that maximize some joint reward function can be modeled as a decentralized partially observable Markov decision proces...
Ranjit Nair, Milind Tambe, Makoto Yokoo, David V. ...
Recent scaling up of decentralized partially observable Markov decision process (DEC-POMDP) solvers towards realistic applications is mainly due to approximate methods. Of this fa...
Researchers in the field of multiagent sequential decision making have commonly used the terms “weakly-coupled” and “loosely-coupled” to qualitatively classify problems i...
Variants of the decentralized MDP model focus on problems exhibiting some special structure that makes them easier to solve in practice. Our work is concerned with two main issues...