Tracing Werewolf Game by Using Extended BDI Model

Abstract

The Werewolf game is a kind of role-playing game in which players have to guess other players' roles from their speech acts (what they say). In this game, players have to estimate other players' beliefs and intentions, and try to modify others' intentions. The BDI model is a suitable one for this game, because it explicitly has notions of mental states, i.e. beliefs, desires and intentions. On the other hand, in this game, players' beliefs are not completely known. Consequently, in many cases it is difficult for players to choose a unique strategy; in other words, players frequently have to maintain probabilistic intentions. However, the conventional BDI model does not have the notion of probabilistic mental states. In this paper, we propose an extension of BDI logic that can handle probabilistic mental states and use it to model some situations in the Werewolf game. We also show examples of deductions concerning those situations. We expect that this study will serve as a basis for developing a Werewolf game agent based on BDI logic in the future.