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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.
Cite As
chun chi (2026). Maze Solver——Q-Learning and SARSA algorithm (https://uk.mathworks.com/matlabcentral/fileexchange/81643-maze-solver-q-learning-and-sarsa-algorithm), MATLAB Central File Exchange. Retrieved .
General Information
- Version 1.0.0 (395 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0 |
