180 citations · 601 across the 46 of their papers we have counts for
3 papers · 2 filters
Scalable Planning and Learning for Multiagent POMDPs: Extended Version
Christopher Amato, Frans A. Oliehoek
Online, sample-based planning algorithms for POMDPs have shown great promise in scaling to problems with large state spaces, but they become intractable for large action and observ…
Incremental Clustering and Expansion for Faster Optimal Planning in Dec-POMDPs
Frans Adriaan Oliehoek, Matthijs T. J. Spaan, Christopher Amato +1
This article presents the state-of-the-art in optimal solution methods for decentralized partially observable Markov decision processes (Dec-POMDPs), which are general models for c…
Policy Iteration for Decentralized Control of Markov Decision Processes
Daniel S. Bernstein, Christopher Amato, Eric A. Hansen +1
Coordination of distributed agents is required for problems arising in many areas, including multi-robot systems, networking and e-commerce. As a formal framework for such problems…