Arxiv Paper – Generative Agent Simulations of 1,000 People

In this episode, we discuss Generative Agent Simulations of 1,000 People by Joon Sung Park, Carolyn Q. Zou, Aaron Shaw, Benjamin Mako Hill, Carrie Cai, Meredith Ringel Morris, Robb Willer, Percy Liang, Michael S. Bernstein. The paper introduces a new agent architecture that simulates the behaviors and attitudes of over 1,000 individuals using large language models and qualitative interviews. The agents effectively replicate personal survey responses with an 85% accuracy rate and are reliable in predicting personality traits and experiment outcomes. This approach also minimizes accuracy biases across different racial and ideological groups, offering a novel method for investigating individual and collective behavior.