Beyond Traditional Gaming: AlphaZero's Triumph in Gomoku Strategy Mastery

  • Abigail Jesse Department of Business, University of Harvard
Keywords: Alpha Zero, Gomoku, Deep Reinforcement Learning, Artificial Intelligence, Game Strategy, Machine Learning, Strategic Decision-Making, Board Games, Advanced AI

Abstract

This study explores the groundbreaking achievement of AlphaZero in mastering Gomoku, a classic board game with intricate strategy dynamics. AlphaZero, a deep reinforcement learning algorithm developed by DeepMind, has demonstrated unparalleled success in various games. The research delves into the strategies employed by AlphaZero in Gomoku, providing insights into advanced AI gaming strategies and their implications beyond traditional gaming. By analyzing AlphaZero's triumph in Gomoku, this study contributes to the broader understanding of artificial intelligence in strategic decision-making and its potential applications in diverse problem-solving domains.

Published
2021-03-30
How to Cite
Abigail Jesse. (2021). Beyond Traditional Gaming: AlphaZero’s Triumph in Gomoku Strategy Mastery. INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 5(2), 204-209. Retrieved from https://ijcst.com.pk/index.php/IJCST/article/view/391