Changyuan Feng, Bin Hong, Jing Hou, and Fugeng Li
Path planning, Q-Learning (QL) algorithm, efficiency
The Q-Learning (QL) algorithm is used to solve path planning problems for the agent. The planning efficiency of the agent is directly affected by the operating speed of the algorithm, which is influenced by various factors. Therefore, based on the QL algorithm, this paper investigates the effects of environment setting on planning efficiency. The results show that when in an obstacle- free environment, the planning efficiency is mainly influenced by the grid number and the relative position of the start point and end point. Moreover, in an obstacle-arranged environment, it is also affected by the obstacle complexity and whether the planning path is on the shortest path.
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