Sabre: A Narrative Planner Supporting Intention and Deep Theory of Mind
Stephen G. Ware, Cory Siler
2021Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment22 citationsDOIOpen Access PDF
Abstract
Sabre is a narrative planner—a centralized, omniscient decision maker that solves a multi-agent storytelling problem. The planner has an author goal it must achieve, but every action taken by an agent must make sense according to that agent's individual intentions and limited, possibly wrong beliefs. This paper describes the implementation of Sabre, which supports a rich action syntax and imposes no arbitrary limit on the depth of theory of mind. We present a search procedure for generating plans that achieve the author goals while ensuring all agent actions are explained, and we report the system's performance on several narrative planning benchmark problems.
Topics & Concepts
PlannerNarrativeStorytellingBenchmark (surveying)Computer scienceAction (physics)SyntaxLimit (mathematics)Artificial intelligenceCognitive sciencePsychologyMathematicsPhilosophyMathematical analysisPhysicsLinguisticsGeodesyQuantum mechanicsGeographyArtificial Intelligence in GamesAI-based Problem Solving and PlanningMulti-Agent Systems and Negotiation