Privacy Preserving Landmark Detection

In many cases several entities, such as commercial companies, need to work together towards the achievement of joint goals, while hiding certain private information. Multi-agent STRIPS (MASTRIPS) is a new and attractive model for describing collaborative multi-agent privacy preserving planning, which is appropriate for such problems. In single agent classical planning, landmarks are key to constructing strong heuristics for state space search. In this paper we propose a method for identifying landmarks in MA-STRIPS in a privacy preserving distributed setting. The agents collaborate to find sound landmarks without revealing their private actions or goals. In addition, we also propose a novel MA-STRIPS planner that uses these landmarks. We empirically show that our detected landmarks improve the performance of previous approaches, and that our new planner is faster than all existing planners for multi-agent problems.