Keeping the Story Straight: A Comparison of Commitment Strategies for a Social Deduction Game

Abstract

Social deduction games present a unique challenge for AI agents, because communication plays a central role in most of them, and deception plays a key role in game play. To be successful in such games, players need to come up with convincing stories, but also discern the truth of statements of other players and adapt to the information learned from them. In this paper we present an approach for virtual agents that have to determine how long to stick to their story in the light of information obtained from other players. We apply this approach to a particular social deduction game, One Night Ultimate Werewolf, and demonstrate the effect of different levels of commitment to an agent's story.