loading
Documents

Research.Publish.Connect.

Paper

Authors: Jan Tožička ; Antonín Komenda and Michal Štolba

Affiliation: Czech Technical University in Prague, Czech Republic

ISBN: 978-989-758-219-6

Keyword(s): Automated Planning, Multiagent Systems, Privacy, Security.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Cooperation and Coordination ; Formal Methods ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Planning and Scheduling ; Privacy, Safety and Security ; Simulation and Modeling ; Symbolic Systems

Abstract: Classical planning can solve large and real-world problems, even when multiple entities, such as robots, trucks or companies, are concerned. But when the interested parties, such as cooperating companies, are interested in maintaining their privacy while planning, classical planning cannot be used. Although, privacy is one of the crucial aspects of multi-agent planning, studies of privacy are underepresented in the literature. A strong privacy property, necessary to leak no information at all, has not been achieved by any planner in general yet. In this contribution, we propose a multiagent planner which can get arbitrarily close to the general strong privacy preserving planner for the price of decreased planning efficiency. The strong privacy assurances are under computational tractability assumptions commonly used in secure computation research.

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 54.159.44.54

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Tožička J., Komenda A. and Štolba M. (2017). ε-Strong Privacy Preserving Multiagent Planner by Computational Tractability.In Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-219-6, pages 51-57. DOI: 10.5220/0006176400510057

@conference{icaart17,
author={Jan Tožička and Antonín Komenda and Michal Štolba},
title={ε-Strong Privacy Preserving Multiagent Planner by Computational Tractability},
booktitle={Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2017},
pages={51-57},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006176400510057},
isbn={978-989-758-219-6},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - ε-Strong Privacy Preserving Multiagent Planner by Computational Tractability
SN - 978-989-758-219-6
AU - Tožička J.
AU - Komenda A.
AU - Štolba M.
PY - 2017
SP - 51
EP - 57
DO - 10.5220/0006176400510057

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.