Solving Maze Problem with Reinforcement Learning by a Mobile Robot
Shih-Wei Lin, Yao-Lin Huang, Wen‐Kuei Hsieh · 2019
Reinforcement learning has been applied to mobile robot control in various domains. In principle, mobile robots can learn through reinforcement learning, but sometimes it can be very time consuming when learning complex tasks. In this paper, three solution algorithms that can be used in the maze problem are introduced. In this paper, we also introduce important mathematical equations in these algorithms.