Chess Engine Based on AI: A Survey

Researchers have been experimenting with several methods to create chess engines that can surpass human players, which has led to a lot of advancement in the field of chess AI in recent years. Neural networks, genetic algorithms, and machine learning are a few of the common methods. Chess engines that use self-play, automatic feature extraction, pattern recognition, and genetic player learning have been created using these methods. Researchers have also looked into various chess AI-related topics, like enhancing the game’s visual appeal, creating multi-player engines, and even creating automated chess commentary. Although each strategy has its advantages and disadvantages, the area of chess AI is still developing as researchers work to create ever-more complex engines that can beat this game.