Machine Learning Comparative analysis of min-max algorithm with alpha-beta pruning optimization for chess engine.

Abstract

The chess game engine is introduced which makes use of a Minmax algorithm for searching game trees and makes use of alpha-beta pruning algorithm to reduce the search space of game states in the game state tree. The first part of this paper is an expository presentation that demonstrates and explains the Minmax algorithm. The paper also proves that the alpha-beta pruning method is shown to make the chess engine algorithm optimal, and bounds are obtained for its running time with various randomized data.