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Genetic Programming
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Genetic programming

Genetic programming (GP) is a subfield of evolutionary computation invented by Nichael Lynn Cramer in 1985 and first explored in depth by John Koza in his 1992 book Genetic Programming: On the Programming of Computers by Means of Natural Selection. It is a method used to allow computer programs to evolve according to some user-defined goal. It uses evolutionary patterns including crossover, selection, replication and mutations to evolve the programs, which are usually represented by Lisp expressions. To work effectively, it requires an appropriate selection of operators and variables.

Genetic programming uses methods which are similar to genetic algorithms (GA), but is based on programs which perform tasks whose results can then be evaluated to deliver a fitness function similar to GAs. Instead of using pools of parameter lists to be evaluated by some evaluation procedure, GP uses pools of programs which are to be run to perform the required task. A technical difference between GAs and GPs is that GAs use list structures, often of fixed size, to store their data, while GPs use tree structures which can vary in size and shape for each program used in the program pools.

The application of a tree representation (and required genetic operators) for using genetic algorithms to generate programs was first described in 1985 by Cramer. Koza, though he did not invent genetic programming, is indisputably the field's most prolific and persuasive author.

So far GPs have successfully solved some toy problems, such as the lawn mower problem, but the method is very computationally intensive, and may not compare favourably where simpler methods, such as genetic algorithms or random optimisation can be used instead. It is possible that some more complex problems may be more amenable to solution using GPs than other optimization methods.

Unfortunately, due to the lack of solid theory regarding the performance of genetic programming vs. traditional search methods (such as hill climbing), genetic programming remains a sort of pariah amongst the various techniques of search. While genetic programming has achieved results that are as good as and sometimes better than human-generated results, more work needs to be done on the theory in order to bring the technique into more widespread use.

Bibliography

  • Cramer, Nichael Lynn (1985), "A representation for the Adaptive Generation of Simple Sequential Programs" in Proceedings of an International Conference on Genetic Algorithms and the Applications, Grefenstette, John J. (ed.), CMU
  • Koza, J.R. (1992), Genetic Programming: On the Programming of Computers by Means of Natural Selection, MIT Press
  • Koza, J.R. (1994), Genetic Programming II: Automatic Discovery of Reusable Programs, MIT Press
  • Koza, J.R., Bennett, F.H., Andre, D., and Keane, M.A. (1999), Genetic Programming III: Darwinian Invention and Problem Solving, Morgan Kaufmann

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Genetic-Programming.org
A definitive source of information about the field of genetic programming with links and conferences.
http://www.genetic-programming.org/

Bibliography on Genetic Programming
A nearly complete bibliography of papers published on genetic programming. Part of the Computer Science Bibliography Collection.
http://liinwww.ira.uka.de/bibliography/Ai/genetic.programming.html

Genetic Programming at University College London
FAQs, people, software, links, conferences, publications, interactive genetic art and music.
http://www.cs.ucl.ac.uk/research/genprog/

Genetic Programming Bibliography
A large single file containing an extensive genetic programming bibliography. Lacks a search function.
http://www.cs.bham.ac.uk/~wbl/biblio/gp-bibliography.html

The Genetic Programming Notebook
A comprehensive directory and tutorial for genetic programming. Includes conferences, researchers, journals, software, and papers.
http://www.geneticprogramming.com/

Events on Artificial Intelligence
List of artificial intelligence conferences, including genetic algorithms.
http://www.drc.ntu.edu.sg/users/mgeorg/enter.epl

Teamwork in Genetic Programming
Thesis and software demonstrating teamwork in genetic programming. Simulates evolving software emulating ants and collective behavior.
http://www.lalena.com/ai/ant/

Cambrian Labs
Developing advanced applications using the art of genetic programming. This technology is primarily being used in research labs, but will certainly find more practical uses.
http://www.cambrianlabs.com/

Liberty Redeployment Technology
LibRT provides professional services and products in the field of information and knowledge technology.
http://www.librt.com

Genetic Programming Inc.
A privately funded research group that does research in applying genetic programming.
http://www.genetic-programming.com/

John R. Koza
Inventor of genetic programming and author of numerous published papers on genetic programming at Stanford University.
http://www.genetic-programming.com/johnkoza.html

GP-96
Genetic Programming 1996 Conference, July 28-31: Stanford University.
http://www.cs.brandeis.edu/~zippy/gp-96.html

International Society for Genetic and Evolutionary Computation
Promotes the creation and exchange of knowledge on Genetic and Evolutionary Computation and their application.
http://www.isgec.org/

Genetic Programming in C++: Implementation Issues
Chapter 13 of Advances in Genetic Programming, Edited by Kenneth E. Kinnear, Jr., MIT Press, 1994.
http://www.frc.ri.cmu.edu/~mcm/chapt.html

Genetic Programming in C/C++
Explains the paradigm of genetic programming, and its implementation in the C/C++ programming language.
http://www.cis.upenn.edu/~hollick/genetic/paper2.html

Groovy Java Genetic Programming
Genetic Programming (JGProg) is an open-source pure Java implementation of a strongly-typed Genetic Programming experimentation platform.
http://jgprog.sourceforge.net/

Journal of Genetic Programming and Evolvable Machines
Devoted to reporting innovative and significant progress in automatic evolution of software and hardware.
http://ls11-www.cs.uni-dortmund.de/people/banzhaf/cfp.html

EuroGP 2002
5th European Conference on Genetic Programming, 3-5 April 2002: Kinsale, Ireland.
http://evonet.dcs.napier.ac.uk/eurogp2002/

GECCO 2002
Genetic and Evolutionary Computation Conference 2002, 9-13 July 2002: New York, NY. A recombination of GP-2002 and ICGA-2002.
http://www-illigal.ge.uiuc.edu:8080/GECCO-2002/

Evolutionary Algorithm Modelling Language
EAML is a modelling language for evolutionary algorithms. It's a XML application and provides the modelling by using XML documents.
http://vision.fhg.de/~veenhuis/EAML/

EVALife's BBase
A literature search engine on Evolutionary Computation and related topics including more than 20000 references.
http://www.evalife.dk/bbase/

Genetic Programming Applied to Text Classification
A graduate-level paper that applies genetic programming to text classification, specifically, filtering e-mail. Available in PDF format only.
http://members.rogers.com/hoomank/papers/katirai99filtering.pdf

Toolkit for Visual Genetic Programming
A GP toolkit for exploring problems which don't have a natural fitness function and need human intuition to select the "best of the breed."
http://www.geom.uiuc.edu/~trowley/genetic/



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