Czech Technical University in Prague, Czech Republic
Automated Planning, Multiagent Systems, Privacy, Security.
Cooperation and Coordination
Informatics in Control, Automation and Robotics
Intelligent Control Systems and Optimization
Planning and Scheduling
Privacy, Safety and Security
Simulation and Modeling
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.