Slice of Life: A Social Physics Game with Interactive Conversations using Symbolically Grounded LLM-Based Generative Dialogue

This paper describes the social physics game Slice of Life.In Slice of Life, the player strives to achieve various social goals by choosing social interactions for characters to engage in.These interactions are governed by a social simulation system called Ensemble with Social Practices (ESP).The ways to achieve the player's social goals are numerous and any given playthrough of the game will result in drastically different social worlds.Slice of Life also makes use of the underlying social simulation system's detailed state to generate symbolically grounded prompts for a large language model (LLM) that generates context-appropriate character dialogue.Rather than using LLMs for novelty or for economic reasons, the underlying social simulation technology, we argue, necessitates this approach in order to make it feasible to have nuanced dialogue that reflects the many ways characters could have gotten themselves into particular social situations.The purpose of this paper is to provide a detailed account of Slice of Life's design, how its social physics simulation enables interactive conversations based on social practices, and to illustrate how the generative possibilities of LLMs can be uniquely useful when applied as its natural language generation (NLG) system, without giving up authorial control of the gameplay or story.