A Framework for Emotion based Adaptive Game State Selection Method using Multivariate Normal Distribution
Keywords:
Adaptive Game Design, Emotional identification, Complex game environment, Normal distribution, Poison distribution, Exponential distribution, Multivariate DatasetAbstract
An adaptive game design is an attractive area for the researchers to participate and contribute more by including various emotional factors, which not only includes emotional factors for a player. The player emotions are directly affect game success factors and the emotions can be measured directly through various facial, speech, and text expressions. This can be indirectly calculated through efficiency of a player by calculating success factor and time to complete each state of a game. In this paper, we have proposed an adaptive game state selection method based on multivariate normal distribution. The proposed method uses two important factor for deciding next state selection from the current level of a game, time to complete one single state and complexity of states within the particular level. The proposed method is a kind of slow-learning technique using multivariate normal distribution method. The experiment evaluation is done by using three different game strategy with 150, 280, and 324 iterations. We have used two other distribution functions for taking accuracy and average error ratio for the proposed method. The performance evaluation shows that the proposed method achieves 79.3 % accuracy and 20.7 % average error ratio. The exponential and poison distribution achieves accuracy of 73.7 % and 72.3 % respectively.
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