AgentGroupChat: An Interactive Group Chat Simulacra For Better Eliciting Emergent Behavior
Zhouhong Gu, Xiaoxuan Zhu, Haoran Guo, Lin Zhang, Yin Cai, Hao Shen,, Jiangjie Chen, Zheyu Ye, Yifei Dai, Yan Gao, Yao Hu, Hongwei Feng, Yanghua, Xiao

TL;DR
AgentGroupChat is a simulation platform that uses large language models to study how language influences emergent collective behaviors in dynamic group scenarios, revealing insights into human societal interactions.
Contribution
This paper introduces AgentGroupChat, a novel interactive simulation leveraging large language models to explore language's role in shaping emergent group behaviors.
Findings
Emergent behaviors arise from environment, diverse traits, and strategic adaptability.
Agents align with human expectations in complex debate scenarios.
Language comprehension and persona influence collective dynamics.
Abstract
Language significantly influences the formation and evolution of Human emergent behavior, which is crucial in understanding collective intelligence within human societies. Considering that the study of how language affects human behavior needs to put it into the dynamic scenarios in which it is used, we introduce AgentGroupChat in this paper, a simulation that delves into the complex role of language in shaping collective behavior through interactive debate scenarios. Central to this simulation are characters engaging in dynamic conversation interactions. To enable simulation, we introduce the Verbal Strategist Agent, utilizing large language models to enhance interaction strategies by incorporating elements of persona and action. We set four narrative scenarios based on AgentGroupChat to demonstrate the simulation's capacity to mimic complex language use in group dynamics. Evaluations…
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Taxonomy
TopicsTechnology Adoption and User Behaviour · Digital Mental Health Interventions · ICT in Developing Communities
MethodsSparse Evolutionary Training · Focus · ALIGN
