Evolutionary Design and Manufacture 2000
DOI: 10.1007/978-1-4471-0519-0_13
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Exploring Component-based Representations - The Secret of Creativity by Evolution?

Abstract: Abstract. This paper investigates one of the newest and most exciting methods in computer science to date: employing computers as creative problem solvers by using evolution to explore for new solutions. The paper introduces and discusses the new understanding that explorative evolution relies upon a representation based on components rather than a parameterisation of a known solution. Evolution explores how the components can be arranged, how many are needed, and the type or function of each. The extra freedo… Show more

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Cited by 26 publications
(9 citation statements)
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“…They have produced solutions that are competitive with, and in some cases superior to, those developed by human experts, and which have resulted in patentable inventions (Koza, 2003;Takagi, 2001;Bentley, 2000;O'Neill and Brabazon, 2009). As such, this domain (in particular analog circuit design (Koza, 2003)) has been a proving ground for the capabilities of an artificial evolutionary process, and has led to arguably the first routinely human-competitive form of machine learning.…”
Section: Introductionmentioning
confidence: 99%
“…They have produced solutions that are competitive with, and in some cases superior to, those developed by human experts, and which have resulted in patentable inventions (Koza, 2003;Takagi, 2001;Bentley, 2000;O'Neill and Brabazon, 2009). As such, this domain (in particular analog circuit design (Koza, 2003)) has been a proving ground for the capabilities of an artificial evolutionary process, and has led to arguably the first routinely human-competitive form of machine learning.…”
Section: Introductionmentioning
confidence: 99%
“…A great deal of recent work has focussed on generative systems and open-ended encodings, and increasingly this is seen as the best route to the creation of the staggering organised complexity found in nature [17], [18], [19]. A chief characteristic of such representations is that phenotypes are "larger" than genotypes, but are organised or patterned in some way.…”
Section: Previous Workmentioning
confidence: 98%
“…The introduction of development to an EA provides a bias to modular iterative structures that already exist in real-world circuit designs whilst allowing evolution to search innovative areas of the search space [59]. Further, introducing development to an evolutionary process may be said to enhance exploration, rather than optimisation of solutions [60].…”
Section: Development and Modularisationmentioning
confidence: 98%