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相关论文: Emergent Social Dynamics of LLM Agents in the El F…

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As autonomous agents become more prevalent, understanding their collective behaviour in strategic interactions is crucial. This study investigates the emergent cooperative tendencies of systems of Large Language Model (LLM) agents in a…

多智能体系统 · 计算机科学 2025-01-28 Richard Willis , Yali Du , Joel Z Leibo , Michael Luck

Can large language model (LLM) agents reproduce the complex social dynamics that characterize human online behavior -- shaped by homophily, reciprocity, and social validation -- and what memory and learning mechanisms enable such dynamics…

人工智能 · 计算机科学 2025-10-23 Philipp J. Schneider , Lin Tian , Marian-Andrei Rizoiu

Recent advancements in Large Language Models (LLMs) have spurred a surge of interest in leveraging these models for game-theoretical simulations, where LLMs act as individual agents engaging in social interactions. This study explores the…

多智能体系统 · 计算机科学 2024-09-04 Ilya Horiguchi , Takahide Yoshida , Takashi Ikegami

The El Farol Bar Problem is a classic computational economics problem in which agents attempt to attend a weekly event at a bar only if it is not too crowded. Each agent has access to multiple competing strategies that may be used to…

适应与自组织系统 · 物理学 2023-06-14 Rebecca E. Cohen , Juan G. Restrepo

As LLMs increasingly act as autonomous agents in interactive and multi-agent settings, understanding their strategic behavior is critical for safety, coordination, and AI-driven social and economic systems. We investigate how payoff…

As LLM-based agents become increasingly autonomous and will more freely interact with each other, studying the interplay among them becomes crucial to anticipate emergent phenomena and potential risks. In this work, we provide an in-depth…

The emergence of Large Language Models (LLMs), has opened exciting possibilities for constructing computational simulations designed to replicate human behavior accurately. Current research suggests that LLM-based agents become increasingly…

计算与语言 · 计算机科学 2024-12-18 Amir Taubenfeld , Yaniv Dover , Roi Reichart , Ariel Goldstein

We study the emergence of agency from scratch by using Large Language Model (LLM)-based agents. In previous studies of LLM-based agents, each agent's characteristics, including personality and memory, have traditionally been predefined. We…

人工智能 · 计算机科学 2024-11-06 Ryosuke Takata , Atsushi Masumori , Takashi Ikegami

Large language models (LLMs) are increasingly used to model human social behavior, with recent research exploring their ability to simulate social dynamics. Here, we test whether LLMs mirror human behavior in social dilemmas, where…

社会与信息网络 · 计算机科学 2024-11-18 Jin Han , Balaraju Battu , Ivan Romić , Talal Rahwan , Petter Holme

Large Language Models (LLMs) have increasingly been utilized in social simulations, where they are often guided by carefully crafted instructions to stably exhibit human-like behaviors during simulations. Nevertheless, we doubt the…

人工智能 · 计算机科学 2024-10-29 Zengqing Wu , Run Peng , Shuyuan Zheng , Qianying Liu , Xu Han , Brian Inhyuk Kwon , Makoto Onizuka , Shaojie Tang , Chuan Xiao

As Large Language Models (LLMs) increasingly operate as autonomous decision-makers in interactive and multi-agent systems and human societies, understanding their strategic behaviour has profound implications for safety, coordination, and…

Rapid advances in large language models (LLMs) have not only empowered autonomous agents to generate social networks, communicate, and form shared and diverging opinions on political issues, but have also begun to play a growing role in…

社会与信息网络 · 计算机科学 2025-05-22 Jinghua Piao , Zhihong Lu , Chen Gao , Fengli Xu , Qinghua Hu , Fernando P. Santos , Yong Li , James Evans

Game-theoretic scenarios have become pivotal in evaluating the social intelligence of Large Language Model (LLM)-based social agents. While numerous studies have explored these agents in such settings, there is a lack of a comprehensive…

计算与语言 · 计算机科学 2025-07-22 Xiachong Feng , Longxu Dou , Ella Li , Qinghao Wang , Haochuan Wang , Yu Guo , Chang Ma , Lingpeng Kong

We discuss a model of heterogeneous, inductive rational agents inspired by the El Farol Bar problem and the Minority Game. As in markets, agents interact through a collective aggregate variable -- which plays a role similar to price --…

统计力学 · 物理学 2009-10-31 Matteo Marsili , Damien Challet , Riccardo Zecchina

Large Language Models (LLMs) have revolutionized Natural Language Processing but exhibit limitations, particularly in autonomously addressing novel challenges such as reasoning and problem-solving. Traditional techniques like…

多智能体系统 · 计算机科学 2024-01-03 Sumedh Rasal

Large Language Models (LLMs) can be deployed in situations where they process positive/negative interactions with other agents. We study how this is done under the sociological framework of social balance, which explains the emergence of…

计算与语言 · 计算机科学 2026-01-07 Pedro Cisneros-Velarde

The evolution of cooperation has been extensively studied using abstract mathematical models and simulations. Recent advances in Large Language Models (LLMs) and the rise of LLM agents have demonstrated their ability to perform social…

As large language models (LLMs) increasingly operate as autonomous agents in social contexts, evaluating their capacity for prosocial behavior is both theoretically and practically critical. However, existing research has primarily relied…

社会与信息网络 · 计算机科学 2025-11-11 Yujia Zhou , Hexi Wang , Qingyao Ai , Zhen Wu , Yiqun Liu

Leveraging Large Language Models (LLMs) for social simulation is a frontier in computational social science. Understanding the social logics these agents embody is critical to this attempt. However, existing research has primarily focused…

人工智能 · 计算机科学 2025-09-29 Haoyang Li , Xiao Jia , Zhanzhan Zhao

Machines driven by large language models (LLMs) have the potential to augment humans across various tasks, a development with profound implications for business settings where effective communication, collaboration, and stakeholder trust…

人机交互 · 计算机科学 2025-07-28 Paweł Niszczota , Tomasz Grzegorczyk , Alexander Pastukhov
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