Developing culture adaptation agent for werewolf games

Abstract

One of the AI systems introduced into our society in recent years is a system that negotiates and collaborates with users by presenting and recommending information through dialogues with multiple users. In general, users have different cultures and values. Therefore, the system must be able to estimate those values and then adapt its behavior to the user. In this study, we focus on the "werewolf game" as a benchmark for this type of technology. The werewolf game is an imperfect information game in which the game proceeds through communication. A werewolf game is a team game and has both cooperative and adversarial characteristics. In werewolf games, it is important not to cause conflicts among allies due to differences in culture and way of thinking. In this study, we first create multiple agent groups with different cultures. Then, we show that there is no specific strong strategy, and that the optimal strategy is different for each group. Then, we build an agent that can estimate the culture of the strategy that players other than itself are following, and can act in such a way that it adapts itself to that culture, and conduct an evaluation based on the winning rate. The results show that the proposed agent is able to adapt to the group and increase its winning rate under certain limitations.