LLM-A*: Large Language Model Enhanced Incremental Heuristic Search on Path Planning
Silin Meng, Yiwei Wang, Cheng-Fu Yang, Nanyun Peng, and Kai-Wei Chang, in Proceedings of the Findings of ACL at The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP-Findings), 2024.
Abstract
Path planning is a fundamental scientific problem in robotics and autonomous navigation. We propose LLM-A*, a novel route planning method that combines the precise pathfinding capabilities of A* with the global reasoning capability of large language models (LLMs). This hybrid approach aims to enhance pathfinding efficiency in terms of time and space complexity while maintaining the integrity of path validity, especially in large-scale scenarios.
Bib Entry
@inproceedings{meng2024llm,
title = {LLM-A*: Large Language Model Enhanced Incremental Heuristic Search on Path Planning},
author = {Meng, Silin and Wang, Yiwei and Yang, Cheng-Fu and Peng, Nanyun and Chang, Kai-Wei},
booktitle = {Proceedings of the Findings of ACL at The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP-Findings)},
year = {2024}
}