The limits of strong privacy preserving multi-agent planning

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00315598" target="_blank" >RIV/68407700:21230/17:00315598 - isvavai.cz</a>

Result on the web

<a href="https://aaai.org/ocs/index.php/ICAPS/ICAPS17/paper/view/15754" target="_blank" >https://aaai.org/ocs/index.php/ICAPS/ICAPS17/paper/view/15754</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

The limits of strong privacy preserving multi-agent planning

Original language description

Multi-agent planning using MA-STRIPS-related models is often motivated by the preservation of private information. Such motivation is not only natural for multi-agent systems, but it is one of the main reasons, why multi-agent planning (MAP) problems cannot be solved centrally. In this paper, we analyze privacy-preserving multi-agent planning (PP-MAP) from the perspective of secure multiparty computation (MPC). We discuss the concept of strong privacy and its implications and present two variants of a novel planner, provably strong privacy-preserving in general. As the main contribution, we formulate the limits of strong privacy-preserving planning in the terms of privacy, completeness and efficiency and show that, for a wide class of planning algorithms, all three properties are not achievable at once. Moreover, we provide a restricted variant of strong privacy based on equivalence classes of planning problems and show that an efficient, complete and strong privacy-preserving planner exists for such restriction.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GJ15-20433Y" target="_blank" >GJ15-20433Y: Heuristic Search for Multiagent and Factored Planning</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings International Conference on Automated Planning and Scheduling, ICAPS

ISBN

978-1-57735-789-6

ISSN

2334-0835

e-ISSN

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Number of pages

9

Pages from-to

297-305

Publisher name

Association for the Advancement of Artificial Intelligence (AAAI)

Place of publication

Palo Alto, California

Event location

Pittsburgh

Event date

Jun 18, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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