A privacy preserving algorithm for multi-agent planning and search

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

45 Scopus citations

Abstract

To engage diverse agents in cooperative behavior, it is important, even necessary, to provide algorithms that do not reveal information that is private or proprietary. A number of recent planning algorithms enable agents to plan together for shared goals without disclosing information about their private state and actions. But these algorithms lack clear and formal privacy guarantees: the fact that they do not require agents to explicitly reveal private information, does not imply that such information cannot be deduced. The main contribution of this paper is an enhanced version of the distributed forward-search planning framework of Nissim and Brafman that reveals less information than the original algorithm, and the first, to our knowledge, discussion and formal proof of privacy guarantees for distributed planning and search algorithms.

Original languageEnglish
Title of host publicationIJCAI 2015 - Proceedings of the 24th International Joint Conference on Artificial Intelligence
EditorsMichael Wooldridge, Qiang Yang
PublisherInternational Joint Conferences on Artificial Intelligence
Pages1530-1536
Number of pages7
ISBN (Electronic)9781577357384
StatePublished - 1 Jan 2015
Event24th International Joint Conference on Artificial Intelligence, IJCAI 2015 - Buenos Aires, Argentina
Duration: 25 Jul 201531 Jul 2015

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
Volume2015-January
ISSN (Print)1045-0823

Conference

Conference24th International Joint Conference on Artificial Intelligence, IJCAI 2015
Country/TerritoryArgentina
CityBuenos Aires
Period25/07/1531/07/15

ASJC Scopus subject areas

  • Artificial Intelligence

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