Maze Solver——Q-Learning and SARSA algorithm

Version 1.0.0 (395 KB) by chun chi
In this project, we simulate two agent by Q-Learning and SARSA algorithm and put them in interactive maze environment to train best strategy
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Updated 23 Oct 2020

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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 (2024). Maze Solver——Q-Learning and SARSA algorithm (https://www.mathworks.com/matlabcentral/fileexchange/81643-maze-solver-q-learning-and-sarsa-algorithm), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2020a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.0.0