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Page-based linear genetic programming

, and . Systems, Man, and Cybernetics, 2000 IEEE International Conference, 5, page 3823--3828. IEEE Press, (8-11 October 2000)

Abstract

Genetic programming arguably represents the most general form of evolutionary computation. However, such generality is not without significant computational overheads. Particularly, the cost of evaluating the fitness of individuals in any form of evolutionary computation represents the single most significant computational bottleneck. A less widely acknowledged computational overhead in GP involves the implementation of the crossover operator. To this end a page-based definition of individuals is used to restrict crossover to equal length code fragments. Moreover, by using a register-machine context, the significance of a priori internal register external output definitions is emphasized.

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