Factored Upper Bounds for Multiagent Planning Problems under Uncertainty with Non-Factored Value Functions

Oliehoek, Frans A ORCID: 0000-0003-4372-5055, Spaan, Matthijs TJ and Witwicki, Stefan J (2015) Factored Upper Bounds for Multiagent Planning Problems under Uncertainty with Non-Factored Value Functions. PROCEEDINGS OF THE TWENTY-FOURTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE (IJCAI), 2015-J. pp. 1645-1651.

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Official URL: http://ijcai.org/proceedings/2015

Abstract

Nowadays, multiagent planning under uncertainty scales to tens or even hundreds of agents. However, current methods either are restricted to problems with factored value functions, or provide solutions without any guarantees on quality. Methods in the former category typically build on heuristic search using upper bounds on the value function. Unfortunately, no techniques exist to compute such upper bounds for problems with non-factored value functions, which would additionally allow for meaningful benchmarking of methods of the latter category. To mitigate this problem, this paper introduces a family of influence-optimistic upper bounds for factored Dec-POMDPs without factored value functions. We demonstrate how we can achieve firm quality guarantees for problems with hundreds of agents.

Item Type:	Article
Subjects:	?? QA75 ??
Depositing User:	Symplectic Admin
Date Deposited:	20 Oct 2015 07:58
Last Modified:	15 Dec 2022 23:33
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/2032540