The Complexity of Decentralized Control of Markov Decision Processes
Mathematics of Operations Research
Taming decentralized POMDPs: towards efficient policy computation for multiagent settings
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
AIS-ADM'07 Proceedings of the 2nd international conference on Autonomous intelligent systems: agents and data mining
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The problem of decentralized control occurs frequently in realistic domains where agents have to cooperate to achieve a universal goal. Planning for domain-level joint strategy takes into account the uncertainty of the underlying environment in computing near-optimal joint-strategies that can handle the intrinsic domain uncertainty. However, uncertainty related to agents deviating from the recommended joint-policy is not taken into consideration. We focus on hostile domains, where the goal is to quickly identify deviations from planned behavior by any compromised agents. There is a growing need to develop techniques that enable the system to recognize and recover from such deviations. We discuss the problem from the intruder's perspective and then present a distributed intrusion detection scheme that can detect a particular type of attack.