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AUTONOMOUS. "Because of the opportunistic nature of empirical credit assignment, the evolved genetic programs are often complex, unreadable and incorporate programming practices that are distinct from strategies used by humans." BINGO! http://scholar.google.es/scholar_url?url=http://citeseerx.ist.psu.edu/viewdoc/download%3Fdoi%3D10.1.1.15.5594%26rep%3Drep1%26type%3Dpdf&hl=en&sa=X&scisig=AAGBfm0J-z_xL5_kjwEhLP0aVOrhbAtTfA&nossl=1&oi=scholarr&ved=0ahUKEwi3wpKxxs_MAhXG2B4KHXRODt0QgAMICigBMAA View in LinkedIn

REPEAT SEQUENCES. "Biological chromosomes are replete with repetitive sequences, micro satellites, SSR tracts, ALU, etc. in their DNA base sequences. We started looking for similar phenomena in evolutionary computation. First studies find copious repeated sequences, which can be hierarchical decomposed into shorter sequences, in programs evolved using both homologous and two point crossover but not with headless chicken crossover or other mutations." https://lnkd.in/eABn2vx View in LinkedIn

PROGRAMMING INTRONS. "The emergence of introns in genetic programing happen as a natural consequence of the dynamics. The superfluous components provide no benefit in terms of fitness to the program but “ride along” with the subtrees they surround." http://scholar.google.es/scholar_url?url=http://citeseerx.ist.psu.edu/viewdoc/download%3Fdoi%3D10.1.1.15.5594%26rep%3Drep1%26type%3Dpdf&hl=en&sa=X&scisig=AAGBfm0J-z_xL5_kjwEhLP0aVOrhbAtTfA&nossl=1&oi=scholarr&ved=0ahUKEwi3wpKxxs_MAhXG2B4KHXRODt0QgAMICigBMAA View in LinkedIn

NONCODING DNA. "Biologists have discovered that there is a vast amount of repetition in the DNA of microbes, plants and animals. Less than 3% of a human genome consists of protein-coding genes but about 50% of it consists of repetitive sequences, many of viral origin." https://lnkd.in/eABn2vx View in LinkedIn

HITCHHIKING. "In genetic algorithms, a set of genes that do not benefit a genotype are said to hitchhike when they are propagated in the population by virtue of other genes in the genotype. Typically, hitchhiking is detrimental to the evolutionary process since the poorer genes that proliferate with the beneficial genes displace their competitors from the population." http://scholar.google.es/scholar_url?url=http://citeseerx.ist.psu.edu/viewdoc/download%3Fdoi%3D10.1.1.15.5594%26rep%3Drep1%26type%3Dpdf&hl=en&sa=X&scisig=AAGBfm0J-z_xL5_kjwEhLP0aVOrhbAtTfA&nossl=1&oi=scholarr&ved=0ahUKEwi3wpKxxs_MAhXG2B4KHXRODt0QgAMICigBMAA View in LinkedIn

UNANTICIPATED. "But rather than rating the content of the trees, as is normally done in genetic algorithms, genetic programs are graded on their behavior when run as a program. Genetic programs often acquire elegant solutions with a degree of subtlety not anticipated by the programmer." http://scholar.google.es/scholar_url?url=http://citeseerx.ist.psu.edu/viewdoc/download%3Fdoi%3D10.1.1.15.5594%26rep%3Drep1%26type%3Dpdf&hl=en&sa=X&scisig=AAGBfm0J-z_xL5_kjwEhLP0aVOrhbAtTfA&nossl=1&oi=scholarr&ved=0ahUKEwi3wpKxxs_MAhXG2B4KHXRODt0QgAMICigBMAA View in LinkedIn

EMERGENT INTRONS. "The advantage of genetic programming introns is that they, they emerge naturally from the dynamics of the algorithm rather than being designed into the representation. It is important then to not impede this emergent property as it may be crucial to the successful development of genetic programs." http://scholar.google.es/scholar_url?url=http://citeseerx.ist.psu.edu/viewdoc/download%3Fdoi%3D10.1.1.15.5594%26rep%3Drep1%26type%3Dpdf&hl=en&sa=X&scisig=AAGBfm0J-z_xL5_kjwEhLP0aVOrhbAtTfA&nossl=1&oi=scholarr&ved=0ahUKEwi3wpKxxs_MAhXG2B4KHXRODt0QgAMICigBMAA View in LinkedIn

"GENETIC PROGRAMMING (GP), a variant of genetic algorithms, is an especially interesting form of computational problem solving. In GP, a population of programs, represented by expression trees in a task specific language, evolve to accomplish the desired task." https://lnkd.in/dcK2gx8 View in LinkedIn

INTRON PADDING. "This could only solve their problem when introns were introduced into the representation. When padding separates expressed components of the bit string, crossover has a better chance of transferring a substring intact. The situation is the same in genetic programs." http://scholar.google.es/scholar_url?url=http://citeseerx.ist.psu.edu/viewdoc/download%3Fdoi%3D10.1.1.15.5594%26rep%3Drep1%26type%3Dpdf&hl=en&sa=X&scisig=AAGBfm0J-z_xL5_kjwEhLP0aVOrhbAtTfA&nossl=1&oi=scholarr&ved=0ahUKEwi3wpKxxs_MAhXG2B4KHXRODt0QgAMICigBMAA View in LinkedIn

REPETITIONS. "There is an advantage from the viewpoint of the evolving genetic program for syntactically redundant constructions that are semantically transparent. Because the redundant functions do not effect the semantics of the sub-expression, if a crossover operation is performed such that it splits the redundant components, the semantics of the removed subtree are still preserved." https://lnkd.in/dcK2gx8 View in LinkedIn