Research on Dynamic Team Formation of Multi-Robots Reinforcement Learning

Abstract

In the field of artificial intelligence, the reinforcement learning theory is receiving more and more attention with the advantage of its self learning and self adaptability With the development of the multi agent theory in distributed artificial intelligence, the distributed reinforcement learning is becoming the focus of this research In this paper, the research status of the reinforcement learning algorithm is illustrated first Then the multi robots' dynamic team formation is used as the study model to illuminate the hierarchical behavior control of the robots system with the usage of the reinforcement learning In the algorithm explained here, the SOM neural network is used to partition the state space automatically to speed up the learning rate The BP neural network is adopted to realize the reinforcement learning to strengthen the generalization ability The inside reinforcement signal and outside reinforcement signal are employed to represent the interest of the individual robot and the group robots respectively In order to define the task, the multi layer control and the blackboard communication are used in the system Finally, the simulation results are provided to show the validity of the algorithm