The field of Genetic Programming (GP) is concerned with harnessing the power of simulated evolution to search massive expression spaces, so as to discover a functional mapping between a non-trivial set of inputs to an arbitrary output. The problems that GP are applied to are often NPComplete and intractable by traditional means.
Citation:
Gearoid Murphy, Conor Ryan, Daniel Howard, "[Seeding Methods for Run Transferable Libraries] Capturing Domain Relevant Functionality through Schematic Manipulation for Genetic Programming," fbit, pp.769-772, 2007 Frontiers in the Convergence of Bioscience and Information Technologies, 2007