A Research on the Generalization Capability of Recursive Backtracking and Binary Tree Algorithm Path Searching: An Experimental Analysis Based on Complex Maze Structures

Lujia Liu

2025

Abstract

Maze path search algorithms are an important area of research in computer science and engineering, with broad application value in many scenarios such as game development and robot navigation. This paper provides a systematic and comprehensive review of the research progress of recursive backtracking algorithms and binary tree algorithms in the field of maze path search, and through experiments, deeply analyzes the principles and key technical bottlenecks of the two types of algorithms in complex maze environments. The paper focuses on issues such as the stack overflow risk of recursive backtracking and the path diversity deficiency of binary tree algorithms, outlining their optimization strategies and research outcomes. Additionally, it provides a detailed exposition of the performance evaluation framework for maze path search algorithms and engineering application cases. Finally, based on the current research landscape, it identifies technical bottlenecks and innovation directions, offering theoretical references for future research and engineering practices in this field.

Paper Citation

in Harvard Style

Liu L. (2025). A Research on the Generalization Capability of Recursive Backtracking and Binary Tree Algorithm Path Searching: An Experimental Analysis Based on Complex Maze Structures. In Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI; ISBN 978-989-758-792-4, SciTePress, pages 482-489. DOI: 10.5220/0014361600004718

in Bibtex Style

@conference{emiti25,
author={Lujia Liu},
title={A Research on the Generalization Capability of Recursive Backtracking and Binary Tree Algorithm Path Searching: An Experimental Analysis Based on Complex Maze Structures},
booktitle={Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI},
year={2025},
pages={482-489},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0014361600004718},
isbn={978-989-758-792-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI
TI - A Research on the Generalization Capability of Recursive Backtracking and Binary Tree Algorithm Path Searching: An Experimental Analysis Based on Complex Maze Structures
SN - 978-989-758-792-4
AU - Liu L.
PY - 2025
SP - 482
EP - 489
DO - 10.5220/0014361600004718
PB - SciTePress