Self-adaptive exploration in evolutionary search

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dc.creatorToussaint, Marc
dc.date2001-02-05
dc.date.accessioned2026-07-07T05:45:25Z
dc.date.available2026-07-07T05:45:25Z
dc.descriptionWe address a primary question of computational as well as biological research on evolution: How can an exploration strategy adapt in such a way as to exploit the information gained about the problem at hand? We first introduce an integrated formalism of evolutionary search which provides a unified view on different specific approaches. On this basis we discuss the implications of indirect modeling (via a ``genotype-phenotype mapping'') on the exploration strategy. Notions such as modularity, pleiotropy and functional phenotypic complex are discussed as implications. Then, rigorously reflecting the notion of self-adaptability, we introduce a new definition that captures self-adaptability of exploration: different genotypes that map to the same phenotype may represent (also topologically) different exploration strategies; self-adaptability requires a variation of exploration strategies along such a ``neutral space''. By this definition, the concept of neutrality becomes a central concern of this paper. Finally, we present examples of these concepts: For a specific grammar-type encoding, we observe a large variability of exploration strategies for a fixed phenotype, and a self-adaptive drift towards short representations with highly structured exploration strategy that matches the ``problem's structure''.
dc.description24 pages, 5 figures
dc.identifierhttps://arxiv.org/abs/physics/0102009
dc.identifierhttp://arxiv.org/abs/physics/0102009
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/83984
dc.subjectBiological Physics
dc.subjectNeural and Evolutionary Computing
dc.subjectAdaptation and Self-Organizing Systems
dc.subjectQuantitative Biology
dc.titleSelf-adaptive exploration in evolutionary search
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