Theses and Dissertations
Date of Award
12-2020
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Computer Science
First Advisor
Dr. Zhixiang Chen
Second Advisor
Dr. Bin Fu
Third Advisor
Dr. Andres Figueroa
Abstract
The game of Gomoku, also called Five in a Row, is an abstract strategy board game. The Gomoku program is constructed upon an algebraic monomial theory to aid values for each possible move and estimate chances for the artificial intelligence program to accomplish a winning path for each move and rounds. With the utilization of the monomial theory, winning configurations are successfully converted into monomials of variables which are represented on board positions. In the artificial intelligence program, an arduous task is how to perform the present configuration of the Gomoku game along with the past moves of the two players. The monomials utilized can generate the artificial intelligence to efficiently interpret the current state and the history of the game. They can also acquiese the artificial intelligence to generate the potential values for future actions from the present state and history of decisions made by the individuals. In extension, implementing the Monte Carlo Tree Search to examine an achievable winning approach for the artificial intelligence. The particular monomials aid to reduce the search capacity in order to benefit estimate rates for analysis of the historical moves and analysis of the future actions. The artificial intelligence Gomoku program with algebraic monomial theory is efficient at high competitive Gomoku. In this current situation, the artificial intelligence can defeat its predecessor and defeat the top rated AI (Wine) ranked 7th in the Gomocup rankings.
Recommended Citation
Garcia, David, "Neural Network Development in an Artificial Intelligence Gomoku Program" (2020). Theses and Dissertations. 667.
https://scholarworks.utrgv.edu/etd/667
Comments
Copyright 2020 David Garcia. All Rights Reserved.
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