In this project, we simulated the interactive maze environment in the MATLAB real-time editor environment, and implemented two classical Rl (reinforcement learning) algorithms - Q-learning and sarsa algorithm. By creating an agent to move interactively in the maze, two algorithms are used to train the highest incentive value reward and the best maze walking method. Finally, we compare the performance of the two algorithms.
引用
chun chi (2026). Maze Solver——Q-Learning and SARSA algorithm (https://jp.mathworks.com/matlabcentral/fileexchange/81643-maze-solver-q-learning-and-sarsa-algorithm), MATLAB Central File Exchange. 取得日: .
MATLAB リリースの互換性
作成:
R2020a
すべてのリリースと互換性あり
プラットフォームの互換性
Windows macOS Linuxタグ
| バージョン | 公開済み | リリース ノート | |
|---|---|---|---|
| 1.0.0 |
