Entries were solicited for cash awards for human-competitive results that were produced by any form of genetic and evolutionary computation and that were published in the open literature during previous year.
Every tree node has an operator function and every terminal node has an operand, making mathematical expressions easy to evolve and evaluate. Thus traditionally GP favors the use of programming languages that naturally embody tree structures for example, Lisp ; other functional programming languages are also suitable.
Non-tree representations have been suggested and successfully implemented, such as linear genetic programming which suits the more traditional imperative languages [see, for example, Banzhaf et al.
Other program representations on which significant Genetic algorithm thesis report and development have been conducted include programs for stack-based virtual machines   and sequences of integers that are mapped to arbitrary programming languages via grammars  .
Cartesian genetic programming is another form of GP, which uses a graph representation instead of the usual tree based representation to encode computer programs.
Most representations have structurally noneffective code introns. Such non-coding genes may seem to be useless, because they have no effect on the performance of any one individual.
However, they alter the probabilities of generating different offspring under the variation operators, and thus alter the individual's variational properties. Experiments seem to show faster convergence when using program representations that allow such non-coding genes, compared to program representations that do not have any non-coding genes.
The individuals are selected probabilistically such that the better performing individuals have a higher chance of getting selected . The most commonly used selection method in GP is Tournament selectionalthough other methods such as Fitness proportionate selectionLexicase Selection and many others have been demonstrated to perform better for many GP problems.
Variation[ edit ] Various genetic operators i. The rate at which these operators are applied determine the diversity in the population. Applications[ edit ] GP has been successfully used as an automatic programming tool, a machine learning tool and an automatic problem-solving engine .
GP is especially useful in the domains where the exact form of the solution is not known in advance or an approximates solution is acceptable possibly because finding the exact solution is very difficult. Some of the applications of GP are curve fitting, data modeling, Symbolic regressionfeature selection, classification, etc.
Koza mentions 76 instances where Genetic Programming has been able to produce results that are competitive with human-produced results called Human-competitive results . Sincethe annual Genetic and Evolutionary Computation Conference GECCO holds Human Competitive Awards called Humies competition where cash awards are presented to human-competitive results produced by any form of genetic and evolutionary computation.
GP has won many awards in this competition over the years. Meta-genetic programming[ edit ] Meta-genetic programming is the proposed meta learning technique of evolving a genetic programming system using genetic programming itself.
It suggests that chromosomes, crossover, and mutation were themselves evolved, therefore like their real life counterparts should be allowed to change on their own rather than being determined by a human programmer.
Doug Lenat 's Eurisko is an earlier effort that may be the same technique.These are the indices in the Main namespace. There is a list of the other namespaces at the bottom of the page. The first annual "Humies" competition was held at the Genetic and Evolutionary Computation Conference (GECCO) in Seattle.
Entries were solicited for cash awards for human-competitive results that were produced by any form of genetic and evolutionary computation and that were published in the open literature during .
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Includes a Java-based demonstration and many links to related research and applications. These are the indices in the Main namespace. There is a list of the other namespaces at the bottom of the page.