计算机与数字工程2025，Vol.53Issue(4)：1086-1090,5.DOI:10.3969/j.issn.1672-9722.2025.04.029
基于改进Sarsa算法的路径规划与障碍物还原
Path Planning and Obstacle Reduction Based on Improved Sarsa Algorithm
刘艳菲 1杨智超1
作者信息
- 1. 江苏大学计算机科学与通信工程学院 镇江 212000
- 折叠
摘要
Abstract
With the popularization of reinforcement learning,it has been gradually applied to mobile communication devices such as agents.However,the communication and transmission of agent devices are often interfered by the surrounding environment.Path planning can effectively improve the reliability of agent communication,but there are many difficulties,so the path planning of agent communication has become one of the research hotspots.In this paper,the classical reinforcement learning algorithm Sarsa is used to study the path planning problem.Aiming at the low efficiency of Sarsa algorithm,an improved Sarsa algorithm based on ob-stacle reduction is proposed.Aiming at the problem of path planning,the optimal path is found to reach the target.Simulation results show that the improved Sarsa algorithm can effectively improve the movement path and work efficiency of the agent.关键词
强化学习/Sarsa算法/路径规划Key words
reinforcement learning/Sarsa algorithm/path planning分类
信息技术与安全科学引用本文复制引用
刘艳菲,杨智超..基于改进Sarsa算法的路径规划与障碍物还原[J].计算机与数字工程,2025,53(4):1086-1090,5.
