The code in this repository aims to solve the Frozen Lake problem, one of the problems in AI gym, using Q-learning and SARSA
The FrozenQLearner.py file contains a base FrozenLearner class and two subclasses FrozenQLearner and FrozenSarsaLearner. These are called by the experiments.py file.
The experiments.py file contains the details of the experiments run using the two algorithms. If the output_file parameter of the methods is set to true a CSV file summarising each session will be written to the outputs directory. The experiments call the FrozenLearner subclasses.
The analysis.R file was used to analyse the output of experiments using charts and some quantitative analysis. The charts are saved to the plots directory in some cases
A python 3.x environment with gym, numpy, sklearn (tested on python 3.5) to run the experiments. An R environment with ggplot2, dplyr, TTR, reshape2, stringr to run the analysis.
The total number of steps and number of random steps
Whether each episode resulted in reaching the goal 'G' or a hole 'H'
The total reward for each episode
