Simulation-Based Simple and Robust Rule Generation for Motion Coordination of Multi-agent System

For motion coordination of a multi-agent system, a simulation-based rule generating method is needed. However, previous studies assuming understandabieness of calculated rules for users do not exist. In this paper, a simulation-based simplified and robust rule generation system for multi-agent scheduling problem is proposed using parallel algorithm discovery and orchestration (PADO) and simulated annealing programming (SAP). In addition, a method to extract constraints of rules from a simulation is also proposed. This proposed method is evaluated with an aircraft control problem, and robust rules can be calculated. Moreover, with the method to extract constraints, the average calculation time can be 80% less than that without the proposed method.