This paper presents the fundamental concepts of inductive Genetic Programming, an evolutionary search method especially suitable for inductive learning tasks. We review the components of the method, and propose new approaches to some open issues such as: the sensitivity of the operators t the topology of the genetic program trees, the coordination of the operators, and the investigation of their performance. The genetic operators are examined by correlation and information analysis of the fitness landscapes. The performance of inductive Genetic Programming is studied with population diversity and evolutionary dynamics measures using hard instances for induction of regular expressions.
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