Many problems of multiagent planning under uncertainty require distributed reasoning with continuous resources and resource limits. Decentralized Markov Decision Problems (Dec-MDP...
Future agent applications will increasingly represent human users autonomously or semi-autonomously in strategic interactions with similar entities. Hence, there is a growing need...
We present a principled and efficient planning algorithm for cooperative multiagent dynamic systems. A striking feature of our method is that the coordination and communication be...
This paper presents properties and results of a new framework for sequential decision-making in multiagent settings called interactive partially observable Markov decision process...
Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are a popular approach for modeling multi-agent systems acting in uncertain domains. Given the signi...
Pradeep Varakantham, Janusz Marecki, Yuichi Yabu, ...