This poster presents a computational model for narrative generation that incorporates Theory of Mind (ToM). It focuses on generating stories where characters have beliefs, desires, and intentions, and where these mental states influence their actions and the plot. The model uses a planning approach with a belief-desire-intention (BDI) architecture to represent character agency and generate coherent narratives. Key aspects include representing character knowledge, reasoning about others' beliefs, and generating actions based on these beliefs. The poster details the model's architecture, implementation, and preliminary evaluation.
Researchers tested large language models (LLMs) and humans on a comprehensive battery of theory of mind tasks, revealing differences in their performance on tasks such as understanding false beliefs, recognizing irony, and identifying faux pas.
