The Rise and Potential of Large Language Model Based Agents: A Survey
- URL: http://arxiv.org/abs/2309.07864v3
- Date: Tue, 19 Sep 2023 08:29:18 GMT
- Title: The Rise and Potential of Large Language Model Based Agents: A Survey
- Authors: Zhiheng Xi, Wenxiang Chen, Xin Guo, Wei He, Yiwen Ding, Boyang Hong,
Ming Zhang, Junzhe Wang, Senjie Jin, Enyu Zhou, Rui Zheng, Xiaoran Fan, Xiao
Wang, Limao Xiong, Yuhao Zhou, Weiran Wang, Changhao Jiang, Yicheng Zou,
Xiangyang Liu, Zhangyue Yin, Shihan Dou, Rongxiang Weng, Wensen Cheng, Qi
Zhang, Wenjuan Qin, Yongyan Zheng, Xipeng Qiu, Xuanjing Huang, Tao Gui
- Abstract summary: Large language models (LLMs) are regarded as potential sparks for Artificial General Intelligence (AGI)
We start by tracing the concept of agents from its philosophical origins to its development in AI, and explain why LLMs are suitable foundations for agents.
We explore the extensive applications of LLM-based agents in three aspects: single-agent scenarios, multi-agent scenarios, and human-agent cooperation.
- Score: 91.71061158000953
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: For a long time, humanity has pursued artificial intelligence (AI) equivalent
to or surpassing the human level, with AI agents considered a promising vehicle
for this pursuit. AI agents are artificial entities that sense their
environment, make decisions, and take actions. Many efforts have been made to
develop intelligent agents, but they mainly focus on advancement in algorithms
or training strategies to enhance specific capabilities or performance on
particular tasks. Actually, what the community lacks is a general and powerful
model to serve as a starting point for designing AI agents that can adapt to
diverse scenarios. Due to the versatile capabilities they demonstrate, large
language models (LLMs) are regarded as potential sparks for Artificial General
Intelligence (AGI), offering hope for building general AI agents. Many
researchers have leveraged LLMs as the foundation to build AI agents and have
achieved significant progress. In this paper, we perform a comprehensive survey
on LLM-based agents. We start by tracing the concept of agents from its
philosophical origins to its development in AI, and explain why LLMs are
suitable foundations for agents. Building upon this, we present a general
framework for LLM-based agents, comprising three main components: brain,
perception, and action, and the framework can be tailored for different
applications. Subsequently, we explore the extensive applications of LLM-based
agents in three aspects: single-agent scenarios, multi-agent scenarios, and
human-agent cooperation. Following this, we delve into agent societies,
exploring the behavior and personality of LLM-based agents, the social
phenomena that emerge from an agent society, and the insights they offer for
human society. Finally, we discuss several key topics and open problems within
the field. A repository for the related papers at
https://github.com/WooooDyy/LLM-Agent-Paper-List.
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