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.

Rule generation method is proposed for an aircraft control problem in an airport. Designing appropriate rules for motion coordination of taxiing aircraft in the airport is important, which is conducted by ground control. However, previous studies did not consider readability of rules, which is important because it should be operated and maintained by humans. Therefore, in this study, using the indicator of readability, we propose a method of rule generation based on parallel algorithm discovery and orchestration (PADO). By applying our proposed method to the aircraft control problem, the proposed algorithm can generate more readable and more robust rules and is found to be superior to previous methods.

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