1A1-F09 Reliability-Based Reinforcement Learning for Multi-Agent Systems : Analyzing Processes of Acquiring Confliction Avoidance Behaviors(Evolution and Learning for Robotics(1))

Abstract

This paper proposes a new reinforcement learning approach for acquiring conflict avoidance behavior in multi-agent systems. To verify the effectivity of the proposed method, we apply the proposed method to the narrow road problem that many agents go by each other in a narrow road. In the narrow road problem, it is the optimal strategy that agents select the different behavior from other agents. The proposed method can differentiate into agents preferring to move forward and agents preferring to give way, by means of the reinforcement learning using reliability parameters.