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This document proposes a new crossover operator called BLX crossover for use in XCS, an evolutionary learning classifier system. BLX crossover combines the innovation power of two-point crossover with local search by allowing the boundaries of classifier rules to move during crossover. Experiments on 12 real-world datasets show that BLX crossover enables XCS to more accurately fit complex decision boundaries compared to two-point crossover, and may prevent overfitting. The work demonstrates the importance of further research on genetic algorithm operators for evolutionary rule discovery.




















