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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

PROGRAMMING INTRONS. "Emergence of Introns in GP. These components are unnecessary since they can be removed from the program without altering the solution the program represents. The ubiquity of redundant constructs suggests a more basic truth about their nature. Introducing introns into a genetic algorithm’s representation improves the success rate as much as a factor of 10." (GP = genetic programming). 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

CONTEXTUAL RESOURCES. "Using emergent intelligence allows the removal of explicit knowledge that is a natural consequence of the problem solving process interacting with the task environment. By allowing the task environment to be an integral component of the problem solving algorithm, all the natural constraints, including those too subtle for a knowledge engineer to extract, are available to the algorithm and emerge at appropriate moments while solving problems." 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

TABLAR RAZAR. "Emergent intelligence (EI) is a method of reducing or removing the reliance on explicit knowledge in a problem solver by favoring instead the emergence of problem specific constraints as a direct consequence of the action of problem solving." 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

OPERATIONS. "All evolutionary computations perform a simple SELECT-COPY-MODIFY loop over the population each generation. SELECT identifies the number of copies each member of the current population produces in the next population based on a relative ranking by the fitness function. COPY makes identical copies of the specified numbers for each member. Finally, MODIFY applies the reproductive operators." 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