異文化体験ゲームにおける集団適応エージェントの開発

Recently, researches of Human-Agent Interaction (HAI) are popular toward autonomous agents to act and cope in various human societies. If agents adapt to humans' society, they should have social skills. These can't be dealt with through conventional methodology of HAI. In this paper, we introduce how developing a social adaptive agent. There are many rules in societies. Therefore, social agents should have a social skill which is obtaining social rules. We develop agents adapting communities as social adaptive agents. We improve some functions from a simulation game: Online BARNGA from BARNGA to observe humans' behavior. We observe humans' behavior in Online BARNGA. As a result, we find that humans have transitions of three inner states with “notice” and “behavior” to get implicit rules, and rules fall into two categories: a byelaw and an ethic. In Online BARNGA, a byelaw is a rule of card game, an ethic is a strategy. We analyzed the brain activities of humans obtaining implicit rules by the functional near infrared spectroscopy technique. As a result, humans' blood flow was decreased at complained by others, and increased at thinking, and it was related to learning. Based on the above results, we develop agents with transitions of three inner states with “notice” and “behavior” and two type learaning modules. Furthermore, we analyze agents' behavior in Online BARNGA, and compare humans' that. As a result, we confirm that the agent adapts socially as if it were human.