This project proposes an evolutionary learning AI agent that learns a winning strategy for the game of Othello using the eXtended Classifier System (XCS) algorithm which is a popular variant of the Learning Classifier System (LCS) algorithm. A research paper has been written on this project and has been accepted in IEEE WCCI-CEC-2018 to be held in Brazil in July, 2018.
The game of Othello has been a favourite in the study of AI due to its simple set of rules, low branching factor and well defined strategic concepts. The LCS system consists of a rule-set which is made to evolve using a combination of Reinforcement Learning (RL) and Genetic Algorithm (GA) such that the evolved rule-set learns an optimal action for each board state.
Following is the snapshot of the GUI of initial state of the Othello board. Simulations can be readily seen on the GUI while the game is running.
Following is the snapshot of the XCS cycle. Various steps in the algorithm have been clearly shown in the cycle.
Final paper would soon be uploaded after getting published with added documentation of the code.