180 citations · 601 across the 46 of their papers we have counts for
4 papers · 1 filter
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…
Planning for Decentralized Control of Multiple Robots Under Uncertainty
Christopher Amato, George D. Konidaris, Gabriel Cruz +3
We describe a probabilistic framework for synthesizing control policies for general multi-robot systems, given environment and sensor models and a cost function. Decentralized, par…
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…