Large Language Model Applied in Multi-agent System—A Survey

Kaiwen Dong

doi:10.54254/2755-2721/109/20241330

Research Article

Open access

Published on 26 November 2024

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Dong,K. (2024). Large Language Model Applied in Multi-agent System—A Survey. Applied and Computational Engineering,109,9-16.

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Large Language Model Applied in Multi-agent System—A Survey

Kaiwen Dong *^,1,

¹ Lancaster University Business School

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/109/20241330

Abstract

The application of large language models (LLMs) in single-agent systems within complex environments has proven successful, prompting a growing interest in their use within multi-agent systems (MAS). Despite the impressive capabilities of LLMs, it remains unclear how they can be optimally integrated and utilized to empower agents in MAS. Understanding how to effectively leverage the advantages of LLMs to enhance agent performance is crucial. This survey provides a comprehensive overview of the application of LLMs in MAS, focusing on their impact on agent cooperation, reasoning, and adaptive abilities. Finally, we discuss future directions and open questions in this evolving field.

Keywords

Multi-agent system, large language model, reinforcement learning.

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Cite this article

Dong,K. (2024). Large Language Model Applied in Multi-agent System—A Survey. Applied and Computational Engineering,109,9-16.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 2nd International Conference on Machine Learning and Automation

Conference website: https://2024.confmla.org/

ISBN：978-1-83558-737-9(Print) / 978-1-83558-738-6(Online)

Conference date: 21 November 2024

Editor：Mustafa ISTANBULLU

Series: Applied and Computational Engineering

Volume number: Vol.109

ISSN：2755-2721(Print) / 2755-273X(Online)

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