首页 /研究 /<title>Evolvability in biologically inspired robotics: solutions for achieving open-ended evolution</title>
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<title>Evolvability in biologically inspired robotics: solutions for achieving open-ended evolution</title>

Chrystopher L. Nehaniv

发表年份
2000
引用次数
5

摘要

We discuss the problem of evolvability in robotic and evolutionary computation systems against the background of biological and more general types of evolution. Open-ended evolution is rigorously defined in terms of unbounded complexity growth and posed as a challenge problem. The first solutions (due to the author) to the problem of open- ended evolution are contained in this paper. These solutions seem unsatisfying but nevertheless are mathematically correct. An implemented solution in software and outlines of solutions in evolving populations of robots and of self-reproducing entities are described. Possible objections to all these solutions are discussed and these point the way to a more sophisticated notion of embodiment with respect to an environment that seems necessary for practical open-ended evolvability.

关键词

EvolvabilityComputer scienceArtificial intelligenceRobotEvolutionary computationArtificial lifeEvolutionary roboticsComputationRoboticsPoint (geometry)

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