Prototyping Slice of Life: Social Physics with Symbolically Grounded LLM-based Generative Dialogue

This paper describes a prototype for the social physics game Slice of Life, and how it makes use of the underlying social simulation system’s sophisticated state to generate symbolically grounded prompts for a large language model (LLM) in order to generate context appropriate character dialogue. Rather than using LLMs for novelty or 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 the characters could have gotten themselves into particular social situations. The primary goal of this paper is to illustrate how the generative possibilities of LLMs can be uniquely useful when applied as a controlled natural language generation (NLG) system, without giving up authorial control of the gameplay or story, or sacrificing accepted good game design practice.