Discovering Deep Building Blocks for Competent Genetic Algorithms Using Chance Discovery via KeyGraphs

In this chapter, we see whether chance discovery in the form of KeyGraphs can be used to reveal deep building blocks for competent genetic algorithms(GAs), thereby speeding up innovation in particularly difficult problems. On an intellectual level, showing the connection between KeyGraphs and genetic algorithms as related pieces of the innovation puzzle is both scientifically and computationally interesting. GAs represent that aspect of human innovation that tries to innovate through the exchange or cross fertilization of notions contained in different ideas; the KeyGraph procedure represents that portion of human innovation that pays special attention to and interprets salient fortuitous events. The chapter goes beyond mere conjecture and performs pilot studies that show how KeyGraphs and competent GAs can work together to solve the problem of deep building blocks; the work is promising and steps toward a practical computational combination of the two procedures are suggested.

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