We introduce point-based dynamic programming (DP) for decentralized partially observable Markov decision processes (DEC-POMDPs), a new discrete DP algorithm for planning strategie...
Decentralized partially observable Markov decision process (DEC-POMDP) is an approach to model multi-robot decision making problems under uncertainty. Since it is NEXP-complete the...
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...
Decentralized partially observable Markov decision processes (Dec-POMDPs) constitute an expressive framework for multiagent planning under uncertainty, but solving them is provabl...
Frans A. Oliehoek, Matthijs T. J. Spaan, Shimon Wh...
Researchers in the field of multiagent sequential decision making have commonly used the terms “weakly-coupled” and “loosely-coupled” to qualitatively classify problems i...