Optimizing Fitness Function for the Game of Go-Moku

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Game playing has been the area of research in Artificial intelligence. Particularly, board game playing programs are often described as being a combination of search and knowledge. Board Games, due to its very nature, provide dynamic environments that make them ideal area of computational intelligence theories, architectures, and algorithms. In board games, it has always been the challenging task to build a quality evaluation function. The goodness or badness of the evaluation function is determined by its accuracy, relevance, cost and outcome. All of these parameters must be addressed and the weighed results are added to an evaluation function experimentally.