強化学習に基づく自律分散システムの制御に関する研究

―環境変化時のエージェント間相互作用の検討―

抄録

In recent years, many systems and robots have been installed in artificial environments such as urban areas and factories.They are also operated in natural environments such as forests and waters.In such places and scenes, the arrangement of people and objects is constantly changing due to their moving, and in addition, there is a possibility that an unknown environment which engineers cannot preliminarily estimate would appear.In order for a plurality of robots to perform stable operations in such unstable environments, some cooperation between the robots must be important.Assuming that the whole is regarded as an autonomous decentralized system in this study, we examine what kind of interactions between multiple robots (agents) can be formed when reinforcement learning based on trial and error is individually applied to each robot (agent).