Principles in the evolutionary design of digital circuits , Part I. genetic programming and evolvabl

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Evolution of Cartesian Genetic Programs for Development of Learning Neural Architecture (2011, methodology): “The characteristics of this type of genotypic redundancy have been investigated in detail and found to be extremely beneficial to the evolutionary process of the problems studied (Miller et al., 2000; Vassilev and Miller, 2000; Yu and Miller, 2001).”
Competitive Coevolution through Evolutionary Complexification (2011, unknown): “Network (Phenotype)”
Redundancy and computational efficiency in Cartesian genetic programming (2006, background): “CGP has been applied to a growing number of domains and problems: digital circuit design [33], [34], digital filter design [31], image processing [48], [70], artificial life [45], bio-inspired developmental models [36]–[38], evolutionary art [3], and molecular docking [12], [13].”
In search of intelligence: evolving a developmental neuron capable of learning (2014, methodology): “The CGP function nodes used here are variants of binary if-statements known as 2 to 1 multiplexers (Miller et al., 2000) with three inputs each, as shown in Figure 2.”
Coevolution of Neuro-developmental Programs That Play Checkers (2008, methodology): “The CGP function nodes we have used are variants of 2 to 1 multiplexers [3] in which data inputs are either inverted or not.”