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Abstract:
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Evolutionary algorithms (EAs) have been applied to an ever increasing variety of problem domains, for which they have achieved human competitive results on small evolutionary design problems. The application of EAs to tasks of ever increasing difficulty is fraught with problems, namely: stagnation of search in large search spaces, negative epistatic effects, disruption of large building blocks, and scalability, amongst others. Recently, the problem of scalability has attracted much attention, and deservedly so, as its resolution is linked to other critical and demanding open research problems such as: development, evolvability, and modularity. In order to improve the scalability of such systems fundamental research must be undertaken to discover how to evolve increasingly more complex designs.
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