Robot soccer confrontation decision-making technology based on MOGM: Multi-objective game model

Abstract

Research on robot soccer confrontation decision-making technology (CDMT) has become a hot spot of the current artificial intelligence and robotics. But the current robot soccer CDMT has the defects of relying on static competition information and lacking the global consciousness. In this paper we propose a novel CDMT based on multi-objective game model (MOGM). MOGM is very suitable to multiple-robot competition. This technology establishes corresponding local information action-based game for every involved soccer robot. Then a global information strategy-based game by the linear weighted sum of the individual robots' local information games is evaluated. Thereby, the proposed method generates the global optimal strategy that meets the requirement of competition situation. The simulation results in Federation International Robot Soccer Association (FIRA) Standard Platform League show that this approach is efficient and reliable.