A chess program basically consists of three main parts, that is, a move generator to generate all legal moves, an evaluation function to evaluate each move, and a search function to select the best move.The core of thinking process is the search function. The search method implemented in this research is alpha beta cutoff. This method is derived from minimax search method to get more optimized.In minimax, all nodes will be searched and compared one by one to get the best value. Meanwhile in alpha beta cutoff, it is not necessary to do those. This method only searches nodes which make contribution to the previous value and cuts off nodes which are not useful. It means that alpha beta will not search and compare all nodes. The new node will be better than the previous one and replace the old value with the new one. In this sense, alpha beta will take less search time.Examinations on this research are by doing a series of matches between human and computer. The results show that the computer has ability to think well and performs a good artificial intelligence though it is very open to be modified and more optimized
note: above is the abstract of my article published by "Indonesian Journal of Computing and Cybernatic System" (IJCCS) Vol. 1 No. 2 Juni 2007
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