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Proceedings of the 4th International Conference on Image, Algorithms, and Artificial Intelligence, ICIAAI 2026, 22-24 May 2026, Singapore, Singapore

Research Article

Exploring the Development Status of Agents Based on Large Language Models

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  • @INPROCEEDINGS{10.4108/eai.22-5-2026.2365080,
        author={Zixi  Chen},
        title={Exploring the Development Status of Agents Based on Large Language Models},
        proceedings={Proceedings of the 4th International Conference on Image, Algorithms, and Artificial Intelligence, ICIAAI 2026, 22-24 May 2026, Singapore, Singapore},
        publisher={EAI},
        proceedings_a={ICIAAI},
        year={2026},
        month={8},
        keywords={LLMs; Agents; Multi-Agent Systems; Embodied Intelligence; Agentic AI},
        doi={10.4108/eai.22-5-2026.2365080}
    }
    
  • Zixi Chen
    Year: 2026
    Exploring the Development Status of Agents Based on Large Language Models
    ICIAAI
    EAI
    DOI: 10.4108/eai.22-5-2026.2365080
Zixi Chen1,*
  • 1: Hainan University, China
*Contact email: chenzixi26offer@163.com

Abstract

The blistering development of Large Language Models (LLMs) is leading to a paradigm shift of artificial intelligence. Of these advancements, agents constructed on the creation of LLM are transforming the models of human-computer interaction and productivity. The given paper is an attempt to analyze the technology of the agents based on the LLM in a systematic way and build a comprehensive framework of cognitions based on micro-level technical systems, up to macro-level patterns of collaboration. It summarizes that the neutralization of the constraints of conventional software can be achieved by the use of the LLM-based agents, which include a set of the brain, planning, memory and the ability to utilize the tools in an unstructured environment. Enterprise-level restructuring, embod intelligence and Agentic AI will be such directions as the development of LLM-based agents in the future.

Keywords
LLMs; Agents; Multi-Agent Systems; Embodied Intelligence; Agentic AI
Published
2026-08-31
Publisher
EAI
http://dx.doi.org/10.4108/eai.22-5-2026.2365080
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