Strategies Game Research Based on Rough Sets Attribute Reduction

摘要

The increasing number of strategies in strategy game has multiplied the calculation complexity. In order to explore this problem, the proposed article has developed a rough sets-game theory model based on attribute reduction. This model utilizes the importance of attributes to evaluate the importance of the opponent's strategies and obtain the minimum reduction set. The minimum reduction set replaces the opponent's original strategy set. The result shows that, this method can short the calculation time and also decrease the computational complexity. When calculating the attributes importance, the decision preferences of opponents are obtained, where different strategies are utilized for opponents. It is helpful for decision makers to formulate strategies based on the opponent's decision preferences. Number example suggests that, this method can reduce the number of opponent's strategies, and decreases the calculation work and the analysis dimension from 4*m to 2*m. The research result can provide useful insights for decision makers.