Multi-competence Cybernetics: The Study of Multiobjective Artificial Systems and Multi-fitness Natural Systems

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

This chapter provides a comparative discussion on natural and artificial systems. It focuses on multiobjective problems as related to the evolution of systems either naturally or artificially; yet, it should be viewed as relevant to other forms of adaptation. Research developments in areas such as evolutionary design, plant biology, robotics, A-life, biotechnology, and game theory are used to support the comparative discussion. A unified approach, namely multi-competence cybernetics (MCC) is suggested. This is followed by a discussion on the relevance of a Pareto approach to the study of nature. One outcome of the current MCC study is a suggested analogy between species and design concepts. Another resulting suggestion is that multi-fitness dynamic visualization of natural systems should be of a scientific value, and in particular for the pursuit of understanding of natural evolution by way of thought experiments. It is hoped, at best, that MCC would direct thinking into fruitful new observations on the multi-fitness aspects of natural adaptation. Alternatively, it is expected that such studies would allow a better understanding of the similarities and dissimilarities between the creation of natural and artificial systems by adaptive processes.

Original languageEnglish
Title of host publicationMultiobjective Problem Solving from Nature
Subtitle of host publicationFrom Concepts to Applications
EditorsJoshua Knowles, David Corne, Kalyanmoy Deb, Deva Raj Chair
Place of PublicationBerlin Heidelberg
PublisherSpringer Science and Business Media Deutschland GmbH
Pages285-304
Number of pages20
ISBN (Electronic)978-3-540-72964-8
ISBN (Print)978-3-540-72963-1
DOIs
StatePublished - 2008

Publication series

NameNatural Computing Series
ISSN (Print)1619-7127

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