240 citations · 674 across the 5 of their papers we have counts for
5 papers
The Complexity of Decentralized Control of Markov Decision Processes
Daniel S Bernstein, Shlomo Zilberstein, Neil Immerman
Planning for distributed agents with partial state information is considered from a decision- theoretic perspective. We describe generalizations of both the MDP and POMDP models th…
Symbolic Generalization for On-line Planning
Zhengzhu Feng, Eric A. Hansen, Shlomo Zilberstein
Symbolic representations have been used successfully in off-line planning algorithms for Markov decision processes. We show that they can also improve the performance of on-line pl…
Region-Based Incremental Pruning for POMDPs
Zhengzhu Feng, Shlomo Zilberstein
We present a major improvement to the incremental pruning algorithm for solving partially observable Markov decision processes. Our technique targets the cross-sum step of the dyna…
MAA*: A Heuristic Search Algorithm for Solving Decentralized POMDPs
Daniel Szer, Francois Charpillet, Shlomo Zilberstein
We present multi-agent A* (MAA*), the first complete and optimal heuristic search algorithm for solving decentralized partially-observable Markov decision problems (DEC-POMDPs) wit…
Decentralized Control of Cooperative Systems: Categorization and Complexity Analysis
C. V. Goldman, S. Zilberstein
Decentralized control of cooperative systems captures the operation of a group of decision makers that share a single global objective. The difficulty in solving optimally such pro…