Computer Chess Using Genetic Algorithm

Chess has always been an intriguing field for a computer programmer. Many techniques and methods have been developed over the years to generate a chess program that is capable of beating the best human chess player. Computers are superior to man when it comes to routine tasks involving math calculations. Chess involves tasks where analysis and instinct are needed and for this reason computers tend to come second when playing a human. In this thesis, a well-known technique for solving optimization problems called Genetic Algorithm is used in a chess program. The main components of a chess program are first reviewed in this thesis. These include Search tree and alpha-beta pruning, etc. Basic genetic algorithm is introduced. An evaluation function is developed using genetic algorithm. This function is used on the chess engine and the performance is evaluated.