Potholes on the Royal Road

dc.creatorBelding, Theodore C.
dc.date2001-04-06
dc.date.accessioned2026-07-07T03:17:04Z
dc.date.available2026-07-07T03:17:04Z
dc.descriptionIt is still unclear how an evolutionary algorithm (EA) searches a fitness landscape, and on what fitness landscapes a particular EA will do well. The validity of the building-block hypothesis, a major tenet of traditional genetic algorithm theory, remains controversial despite its continued use to justify claims about EAs. This paper outlines a research program to begin to answer some of these open questions, by extending the work done in the royal road project. The short-term goal is to find a simple class of functions which the simple genetic algorithm optimizes better than other optimization methods, such as hillclimbers. A dialectical heuristic for searching for such a class is introduced. As an example of using the heuristic, the simple genetic algorithm is compared with a set of hillclimbers on a simple subset of the hyperplane-defined functions, the pothole functions.
dc.description8 pages; to appear in GECCO 2001
dc.identifierhttps://arxiv.org/abs/cs/0104011
dc.identifierhttp://arxiv.org/abs/cs/0104011
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/30587
dc.subjectNeural and Evolutionary Computing
dc.subjectAdaptation and Self-Organizing Systems
dc.subjectI.2.m
dc.titlePotholes on the Royal Road
dc.typetext

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