Learning Classifier System Ensembles With Rule-Sharing
IEEE Transactions on Evolutionary Computation
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This paper presented a novel approach to solving the problem of robot path planning. A Learning Classifier System is an accuracy-based machine learning system that combines covering operator and genetic algorithm. The covering operator is responsible for adjusting precision and large search space according to some reward obtained from the environment. The genetic algorithm acts as an innovation discovery component which is responsible for discovering new better path planning rules. The advantages of this approach are its accuracy-based representation that can easily reduce learning space, improve online learning ability, robustness due to the use of genetic algorithm.