Joon Sung Park [email protected], Joseph C O'brien [email protected], Carrie J Cai [email protected], Meredith Ringel Morris [email protected], M.SPercy Liang [email protected], Michael S Bernstein, Bernstein, Generative, Stanford University Stanford USA, Stanford University Stanford USA, Google Research Mountain View CAUSA, Google DeepMind Seattle WAUSA, Stanford University Stanford USA, Stanford University Stanford USA, UIST '23 October 29-November 12023San FranciscoCAUSA, UIST '23 October 29-November 12023San FranciscoCAUSA, 2023San FranciscoCAUSA (2023)
This paper introduces generative agents designed to simulate believable human behavior in an interactive environment, inspired by sandbox games like The Sims. The authors propose an architecture enabling agents to store, retrieve, reflect on memories, and interact with each other dynamically. The architecture consists of a memory stream, reflection, and planning components that collectively support believable behavior across various contexts. The authors conducted evaluations to demonstrate that these agents can engage in individual and emergent social behaviors. The findings suggest that generative agents can effectively manage complexities of human interactions and create immersive environments beneficial for various applications like social role-play and virtual environment simulations. The paper also discusses potential societal impacts, applications, future improvements, and ethical considerations surrounding the use of generative agents.
This paper employs the following methods:
The following datasets were used in this research:
The authors identified the following limitations: