A survey on large language model based autonomous agents

• DOI: 10.1007/s11704-024-40231-1
• Publication Date: 2024-03-22T23:01:20Z
• Authors: Lei Wang; Chen Ma; Xueyang Feng; Zeyu Zhang; Hao Yang; Jingsen Zhang; Zhiyuan Chen; Jiakai Tang; Xu Chen; Yankai Lin; Wayne Xin Zhao; Zhewei Wei; Jirong Wen
• Keywords: 0301 basic medicine; FOS: Computer and information sciences; 03 medical and health sciences; Computer Science - Computation and Language; Artificial Intelligence (cs.AI); Computer Science - Artificial Intelligence; Computation and Language (cs.CL)

Abstract Autonomous agents have long been a research focus in academic and industry communities. Previous often focuses on training with limited knowledge within isolated environments, which diverges significantly from human learning processes, makes the hard to achieve human-like decisions. Recently, through acquisition of vast amounts Web knowledge, large language models (LLMs) shown potential human-level intelligence, leading surge LLM-based autonomous agents. In this paper, we present comprehensive survey these studies, delivering systematic review holistic perspective. We first discuss construction agents, proposing unified framework that encompasses much previous work. Then, overview diverse applications social science, natural engineering. Finally, delve into evaluation strategies commonly used for Based also several challenges future directions field.