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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 have social skills. 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 group 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 rdquonoticerdquo and rdquobehaviorrdquo 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. Based on the above results, we develop agents with transitions of three inner state with rdquonoticerdquo and rdquobehaviorrdquo and two type learning modules. Furthermore, we analyze agents' behavior in online BARNGA, and compare humans' that. As a result, we confirm that agent adapt socially as if it were human.