AgentGroupChat: An Interactive Group Chat Simulacra For Better Eliciting Emergent Behavior
arxiv(2024)
摘要
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 focus on
aligning agent behaviors with human expectations and the emergence of
collective behaviors within the simulation. Results reveal that emergent
behaviors materialize from a confluence of factors: a conducive environment for
extensive information exchange, characters with diverse traits, high linguistic
comprehension, and strategic adaptability. During discussions on “the impact
of AI on humanity” in AgentGroupChat simulation, philosophers commonly agreed
that “AI could enhance societal welfare with judicious limitations” and even
come to a conclusion that “the essence of true intelligence encompasses
understanding the necessity to constrain self abilities”. Additionally, in the
competitive domain of casting for primary roles in films in AgentGroupChat,
certain actors were ready to reduce their remuneration or accept lesser roles,
motivated by their deep-seated desire to contribute to the project.
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