Survey on Intelligent Planning Methods from Large Language Models Perspective

Authors

Yanzhong Zhou, College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China
Junren Luo, College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China
Xueqiang Gu, College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China
Wanpeng Zhang, College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China

Abstract

Abstract: Starting from the perspective of large language models, this paper gives an overview of the definition and development of intelligent planning, and briefly introduces the traditional methods of intelligent planning; based on the close relationship between large language model intelligent agents and intelligent planning, introduces the architecture of large language models and typical large model intelligent agents; focusing on the intelligent planning for large language models, combs through the learning of planning languages, chain of thought, feedback optimization, and process automation; combining with the current challenges and difficulties, introduces the outlook of cutting-edge research on intelligent planning with large models.

Recommended Citation

Zhou, Yanzhong; Luo, Junren; Gu, Xueqiang; and Zhang, Wanpeng (2025) "Survey on Intelligent Planning Methods from Large Language Models Perspective," Journal of System Simulation: Vol. 37: Iss. 4, Article 1.
DOI: 10.16182/j.issn1004731x.joss.23-1468
Available at: https://dc-china-simulation.researchcommons.org/journal/vol37/iss4/1

First Page

823

Last Page

844

CLC

TP391

Recommended Citation

Zhou Yanzhong, Luo Junren, Gu Xueqiang, et al. Survey on Intelligent Planning Methods from Large Language Models Perspective[J]. Journal of System Simulation, 2025, 37(4): 823-844.

Corresponding Author

Zhang Wanpeng

DOI

10.16182/j.issn1004731x.joss.23-1468