Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
IWLCS '00 Revised Papers from the Third International Workshop on Advances in Learning Classifier Systems
Fast rule matching for learning classifier systems via vector instructions
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Classifier fitness based on accuracy
Evolutionary Computation
An analysis of matching in learning classifier systems
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Speeding up the evaluation of evolutionary learning systems using GPGPUs
Proceedings of the 12th annual conference on Genetic and evolutionary computation
A simple multi-core parallelization strategy for learning classifier system evaluation
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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Computing the system prediction is one of the most important and computationally expensive tasks in Learning Classifier Systems. In this paper, we provide a parallel solution to the problem of computing the prediction array in XCS using the NVIDIA's Compute Unified Device Architecture (CUDA). We performed several experiments to test our parallel solution using two different types of GPUs and to study how performances are affected by (i) the problem size, (ii) the number of problem actions, and (iii) the number of classifiers in the population. Our experimental results show a speedup that ranges from slightly less than 2X up to 32X.