Abstract: In this paper, we consider a multi-pursuer single-superior-evader pursuit-evasion game where the evader has a speed that is similar to or higher than the speed of each pursuer. A new fuzzy rein- forcement learning algorithm is proposed in this work. The proposed algorithm uses the well-known Apollonius circle mechanism to define the capture region of the learning pursuer based on its loca- tion and the location of the superior evader. The proposed algorithm uses the Apollonius circle with a developed formation control approach in the tuning mechanism of the fuzzy logic controller (FLC) of the learning pursuer so that one or some of the learning pursuers can capture the superior evader. The formation control mechanism used by the proposed algorithm guarantees that the pursuers are distributed around the superior evader in order to avoid collision between pursuers. The formation con- trol mechanism used by the proposed algorithm also makes the Apollonius circles of each two adjacent pursuers intersect or be at least tangent to each other so that the capture of the superior evader can occur. The proposed algorithm is a decentralized algorithm as no communication among the pursuers is required. The only information the proposed algorithm requires is the position and the speed of the superior evader. The proposed algorithm is used to learn different multi-pursuer single-superior-evader pursuit-evasion games. The simulation results show the effectiveness of the proposed algorithm. PDF
Keywords: Fuzzy control, Reinforcement learning, Pursuit-evasion differential games, Apollonius circles.