Computational Multi-Agents Society Experiments: Social Modeling Framework Based on Generative Agents

TL;DR

CMASE is a novel framework combining generative agent-based modeling with virtual ethnography to enable real-time, embedded social experiments and interventions in virtual environments, enhancing understanding of complex social phenomena.

Contribution

This paper introduces CMASE, a new framework that integrates ethnographic methods with computational modeling for embedded, interactive social simulations.

Findings

CMASE can simulate complex social phenomena accurately.

Behavior trajectories generated are consistent with statistical and mechanistic explanations.

The framework supports real-time human-computer interaction for social intervention modeling.

Abstract

This paper introduces CMASE, a framework for Computational Multi-Agent Society Experiments that integrates generative agent-based modeling with virtual ethnographic methods to support researcher embedding, interactive participation, and mechanism-oriented intervention in virtual social environments. By transforming the simulation into a simulated ethnographic field, CMASE shifts the researcher from an external operator to an embedded participant. Specifically, the framework is designed to achieve three core capabilities: (1) enabling real-time human-computer interaction that allows researchers to dynamically embed themselves into the system to characterize complex social intervention processes; (2) reconstructing the generative logic of social phenomena by combining the rigor of computational experiments with the interpretative depth of traditional ethnography; and (3) providing a predictive foundation with causal explanatory power to make forward-looking judgments without sacrificing empirical accuracy. Experimental results show that CMASE can not only simulate complex phenomena, but also generate behavior trajectories consistent with both statistical patterns and mechanistic explanations. These findings demonstrate CMASE's methodological value for intervention modeling, highlighting its potential to advance interdisciplinary integration in the social sciences. The official code is available at: https://github.com/armihia/CMASE .