A Pattern Based Evolutionary Approach to Prediction Computation in XCSF
XCSF is a new version of XCS with the ability of computing the environmental rewards. In the early versions of XCSF, this computation was done by approximating the coefficients of the associated polynomial reward functions. However, recent researches show that this approximation method suffers from some significant drawbacks such as input range dependency. In this paper, we propose a new method to approximate the reward functions using Genetic Algorithms. Our proposed method uses a new representation scheme for chromosomes and some newly introduced pattern based operators which are adapted for function approximation.
KeywordsBenchmark Problem Reward Function Mean Absolute Error Input Range Good Chromosome
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