Heterogeneous Learning Using Genetic Algorithms

Heterogeneous Learning Using Genetic Algorithms

T. Vallee (LEN, Nantes University, France)
DOI: 10.4018/978-1-59140-984-7.ch018
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Abstract

The goal of this chapter is twofold. First, assuming that all agents belong to a genetic population, the evolution of inflation learning will be studied using a heterogeneous genetic learning process. Second, by using real-floating-point coding and different genetic operators, the quality of the learning tools and their possible impact on the learning process will be examined.

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