Authors:
Jan Tožička
;
Antonín Komenda
and
Michal Štolba
Affiliation:
Czech Technical University in Prague, Czech Republic
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.