Spontaneous Emergence of Agent Individuality Through Social Interactions in Large Language Model-Based Communities
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 focused on how individuality, such as behavior, personality,...
| 發表在: | Entropy |
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| Main Authors: | , , |
| 格式: | Article |
| 語言: | 英语 |
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MDPI AG
2024-12-01
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| 主題: | |
| 在線閱讀: | https://www.mdpi.com/1099-4300/26/12/1092 |
| _version_ | 1849520640326893568 |
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| author | Ryosuke Takata Atsushi Masumori Takashi Ikegami |
| author_facet | Ryosuke Takata Atsushi Masumori Takashi Ikegami |
| author_sort | Ryosuke Takata |
| collection | DOAJ |
| container_title | Entropy |
| description | 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 focused on how individuality, such as behavior, personality, and memory, can be differentiated from an undifferentiated state. The present LLM agents engage in cooperative communication within a group simulation, exchanging context-based messages in natural language. By analyzing this multi-agent simulation, we report valuable new insights into how social norms, cooperation, and personality traits can emerge spontaneously. This paper demonstrates that autonomously interacting LLM-powered agents generate hallucinations and hashtags to sustain communication, which, in turn, increases the diversity of words within their interactions. Each agent’s emotions shift through communication, and as they form communities, the personalities of the agents emerge and evolve accordingly. This computational modeling approach and its findings will provide a new method for analyzing collective artificial intelligence. |
| format | Article |
| id | doaj-art-e89c1b6f50fa44a2bc2026fa031f4793 |
| institution | Directory of Open Access Journals |
| issn | 1099-4300 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| spelling | doaj-art-e89c1b6f50fa44a2bc2026fa031f47932025-08-20T02:53:19ZengMDPI AGEntropy1099-43002024-12-012612109210.3390/e26121092Spontaneous Emergence of Agent Individuality Through Social Interactions in Large Language Model-Based CommunitiesRyosuke Takata0Atsushi Masumori1Takashi Ikegami2Graduate School of Arts and Sciences, University of Tokyo, Tokyo 153-8902, JapanGraduate School of Arts and Sciences, University of Tokyo, Tokyo 153-8902, JapanGraduate School of Arts and Sciences, University of Tokyo, Tokyo 153-8902, JapanWe 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 focused on how individuality, such as behavior, personality, and memory, can be differentiated from an undifferentiated state. The present LLM agents engage in cooperative communication within a group simulation, exchanging context-based messages in natural language. By analyzing this multi-agent simulation, we report valuable new insights into how social norms, cooperation, and personality traits can emerge spontaneously. This paper demonstrates that autonomously interacting LLM-powered agents generate hallucinations and hashtags to sustain communication, which, in turn, increases the diversity of words within their interactions. Each agent’s emotions shift through communication, and as they form communities, the personalities of the agents emerge and evolve accordingly. This computational modeling approach and its findings will provide a new method for analyzing collective artificial intelligence.https://www.mdpi.com/1099-4300/26/12/1092large language modelagent-based simulationcollective intelligence |
| spellingShingle | Ryosuke Takata Atsushi Masumori Takashi Ikegami Spontaneous Emergence of Agent Individuality Through Social Interactions in Large Language Model-Based Communities large language model agent-based simulation collective intelligence |
| title | Spontaneous Emergence of Agent Individuality Through Social Interactions in Large Language Model-Based Communities |
| title_full | Spontaneous Emergence of Agent Individuality Through Social Interactions in Large Language Model-Based Communities |
| title_fullStr | Spontaneous Emergence of Agent Individuality Through Social Interactions in Large Language Model-Based Communities |
| title_full_unstemmed | Spontaneous Emergence of Agent Individuality Through Social Interactions in Large Language Model-Based Communities |
| title_short | Spontaneous Emergence of Agent Individuality Through Social Interactions in Large Language Model-Based Communities |
| title_sort | spontaneous emergence of agent individuality through social interactions in large language model based communities |
| topic | large language model agent-based simulation collective intelligence |
| url | https://www.mdpi.com/1099-4300/26/12/1092 |
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