Driving Generative Agents With Their Personality

arXiv:2402.14879v1 Announce Type: new
Abstract: This research explores the potential of Large Language Models (LLMs) to utilize psychometric values, specifically personality information, within the context of video game character development. Affective Computing (AC) systems quantify a Non-Player character's (NPC) psyche, and an LLM can take advantage of the system's information by using the values for prompt generation. The research shows an LLM can consistently represent a given personality profile, thereby enhancing the human-like characteristics of game characters. Repurposing a human …

abstract agents arxiv computing context cs.ai cs.cl development driving game generative information language language models large language large language models llm llms personality research systems type values video video game