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Optimizing Search Space of Othello Using Hybrid Approach

Publication Date : 31/07/2014

Author(s) :

Chetan Chudasama , Pramod Tripathi , Keyur Prajapati.

Volume/Issue :
Volume 1
Issue 1
(07 - 2014)

Abstract :

One of the areas of Artificial Intelligence is Game Playing. Game playing programs are often described as being a combination of search and knowledge. The board games are very popular. Board games provide dynamic environments that make them ideal area of computational intelligence theories. Othello is 8 × 8 board game and it has very huge state space as 364 ≈ 1028 total states. It is implemented by game search tree like Mini-max algorithm, alpha-beta pruning. But it required more storage memory and more time to compute best move among all valid moves. Evolutionary algorithms such as Genetic algorithm are applied to the game playing because of the very large state space of the problem. Game search tree algorithm like alpha- beta pruning is used to build efficient computer player program. This paper mainly highlights on hybrid approach which is combination of Genetic algorithm and alpha-beta pruning. Genetic algorithm is applied to optimize search space of Othello game and building Genetic Weight Vector. This weight vector is applied to game which played by alpha- beta pruning game search tree algorithm. And we optimize search space of Othello and get best move in less amount of time.

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Optimizing Search Space of Othello Using Hybrid Approach

December 2, 2014