This Q-Learning code for MATLAB has been written by Ioannis Makris and Andrew Chalikiopoulos. It trains an agent to find the shortest way through a 25x25 maze. Following convergence of the algorithm, MATLAB will print out the shortest path to the goal and will also create three graphs to measure the performance of the agent.

Filename	Size	Update
Q-Learning-Algorithm-Implementation-in-MATLAB-master	0	2015-05-09
Q-Learning-Algorithm-Implementation-in-MATLAB-master\LICENSE	18047	2015-05-09
Q-Learning-Algorithm-Implementation-in-MATLAB-master\README.md	3677	2015-05-09
Q-Learning-Algorithm-Implementation-in-MATLAB-master\RandomPermutation.m	858	2015-05-09
Q-Learning-Algorithm-Implementation-in-MATLAB-master\ReinforcementLearningGreedy.m	5801	2015-05-09
Q-Learning-Algorithm-Implementation-in-MATLAB-master\ReinforcementLearningUpdateR.m	5921	2015-05-09
Q-Learning-Algorithm-Implementation-in-MATLAB-master\ReinforcementLearning_RandomPol.m	4448	2015-05-09
Q-Learning-Algorithm-Implementation-in-MATLAB-master\RewardMatrix100.m	166	2015-05-09
Q-Learning-Algorithm-Implementation-in-MATLAB-master\RewardMatrix25.m	4046	2015-05-09
Q-Learning-Algorithm-Implementation-in-MATLAB-master\RewardMatrixNoPunishment.csv	49411	2015-05-09
Q-Learning-Algorithm-Implementation-in-MATLAB-master\RewardMatrixPunishment.csv	49284	2015-05-09

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