Difference between revisions of "Genetic Programming"

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* [[Edward P. Manning]] ('''2010'''). ''[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5409565 Using Resource-Limited Nash Memory to Improve an Othello Evaluation Function]''. [[IEEE#TOCIAIGAMES|IEEE Transactions on Computational Intelligence and AI in Games]], Vol. 2, No. 1 » [[Othello]]
 
* [[Edward P. Manning]] ('''2010'''). ''[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5409565 Using Resource-Limited Nash Memory to Improve an Othello Evaluation Function]''. [[IEEE#TOCIAIGAMES|IEEE Transactions on Computational Intelligence and AI in Games]], Vol. 2, No. 1 » [[Othello]]
 
* [[Edward P. Manning]] ('''2010'''). ''[http://dl.acm.org/citation.cfm?id=1830667 Coevolution in a Large Search Space using Resource-limited Nash Memory]''. [http://www.informatik.uni-trier.de/~ley/db/conf/gecco/gecco2010.html#Manning10 GECCO '10] » [[Othello]]
 
* [[Edward P. Manning]] ('''2010'''). ''[http://dl.acm.org/citation.cfm?id=1830667 Coevolution in a Large Search Space using Resource-limited Nash Memory]''. [http://www.informatik.uni-trier.de/~ley/db/conf/gecco/gecco2010.html#Manning10 GECCO '10] » [[Othello]]
 +
* [[Ilya Loshchilov]], [[Marc Schoenauer]], [[Michèle Sebag]] ('''2010'''). ''A mono surrogate for multiobjective optimization''. [https://dblp.org/db/conf/gecco/gecco2010.html GECCO 2010], [https://hal.inria.fr/inria-00483948/document pdf]
 
'''2011'''
 
'''2011'''
 
* [https://dblp.uni-trier.de/pers/hd/f/Fogel:Gary_B= Gary B. Fogel], [[David B. Fogel]], [https://dblp.uni-trier.de/pers/hd/f/Fogel:Lawrence_J= Lawrence J. Fogel] ('''2011'''). ''[http://www.scholarpedia.org/article/Evolutionary_programming Evolutionary programming]''. [https://en.wikipedia.org/wiki/Scholarpedia Scholarpedia], Vol. 6, No. 4
 
* [https://dblp.uni-trier.de/pers/hd/f/Fogel:Gary_B= Gary B. Fogel], [[David B. Fogel]], [https://dblp.uni-trier.de/pers/hd/f/Fogel:Lawrence_J= Lawrence J. Fogel] ('''2011'''). ''[http://www.scholarpedia.org/article/Evolutionary_programming Evolutionary programming]''. [https://en.wikipedia.org/wiki/Scholarpedia Scholarpedia], Vol. 6, No. 4
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* [[Paweł Liskowski]] ('''2012'''). ''Co-Evolution versus Evolution with Random Sampling for Acquiring Othello Position Evaluation''. master's thesis, [https://en.wikipedia.org/wiki/Pozna%C5%84_University_of_Technology Poznań University of Technology], supervisor [[Wojciech Jaśkowski]], [http://www.cs.put.poznan.pl/wjaskowski/pub/var/pliskowski_msc.pdf pdf]  » [[Othello]]
 
* [[Paweł Liskowski]] ('''2012'''). ''Co-Evolution versus Evolution with Random Sampling for Acquiring Othello Position Evaluation''. master's thesis, [https://en.wikipedia.org/wiki/Pozna%C5%84_University_of_Technology Poznań University of Technology], supervisor [[Wojciech Jaśkowski]], [http://www.cs.put.poznan.pl/wjaskowski/pub/var/pliskowski_msc.pdf pdf]  » [[Othello]]
 
* [[Marcin Szubert]], [[Krzysztof Krawiec]]  ('''2012'''). ''[http://link.springer.com/chapter/10.1007/978-3-642-32964-7_22 Autonomous Shaping via Coevolutionary Selection of Training Experience]''. [http://www.informatik.uni-trier.de/~ley/db/conf/ppsn/ppsn2012-2.html#SzubertK12 12. PPSN]
 
* [[Marcin Szubert]], [[Krzysztof Krawiec]]  ('''2012'''). ''[http://link.springer.com/chapter/10.1007/978-3-642-32964-7_22 Autonomous Shaping via Coevolutionary Selection of Training Experience]''. [http://www.informatik.uni-trier.de/~ley/db/conf/ppsn/ppsn2012-2.html#SzubertK12 12. PPSN]
 +
* [[Ilya Loshchilov]], [[Marc Schoenauer]], [[Michèle Sebag]] ('''2012'''). ''Self-Adaptive Surrogate-Assisted Covariance Matrix Adaptation Evolution Strategy''. [https://arxiv.org/abs/1204.2356 arXiv:1204.2356]
 +
* [[Ilya Loshchilov]], [[Marc Schoenauer]], [[Michèle Sebag]] ('''2012'''). ''Alternative Restart Strategies for CMA-ES''. [https://arxiv.org/abs/1207.0206 arXiv:1207.0206]
 
'''2013'''
 
'''2013'''
 
* [[Marcin Szubert]], [[Wojciech Jaśkowski]], [[Krzysztof Krawiec]] ('''2013'''). ''[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6504736 On Scalability, Generalization, and Hybridization of Coevolutionary Learning: a Case Study for Othello]''. [[IEEE#TOCIAIGAMES|IEEE Transactions on Computational Intelligence and AI in Games]], Vol. 5, No. 3 » [[Othello]]
 
* [[Marcin Szubert]], [[Wojciech Jaśkowski]], [[Krzysztof Krawiec]] ('''2013'''). ''[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6504736 On Scalability, Generalization, and Hybridization of Coevolutionary Learning: a Case Study for Othello]''. [[IEEE#TOCIAIGAMES|IEEE Transactions on Computational Intelligence and AI in Games]], Vol. 5, No. 3 » [[Othello]]
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* [[Wojciech Jaśkowski]], [[Paweł Liskowski]], [[Marcin Szubert]], [[Krzysztof Krawiec]] ('''2013'''). ''Improving Coevolution by Random Sampling''. [http://www.informatik.uni-trier.de/~ley/db/conf/gecco/gecco2013.html#JaskowskiLSK13 GECCO 2013], [http://www.cs.put.poznan.pl/mszubert/pub/jaskowski2013gecco.pdf pdf]
 
* [[Wojciech Jaśkowski]], [[Paweł Liskowski]], [[Marcin Szubert]], [[Krzysztof Krawiec]] ('''2013'''). ''Improving Coevolution by Random Sampling''. [http://www.informatik.uni-trier.de/~ley/db/conf/gecco/gecco2013.html#JaskowskiLSK13 GECCO 2013], [http://www.cs.put.poznan.pl/mszubert/pub/jaskowski2013gecco.pdf pdf]
 
* [[S. Ali Mirsoleimani]], [http://dblp.uni-trier.de/pers/hd/k/Karami:Ali Ali Karami], [http://dblp.uni-trier.de/pers/hd/k/Khunjush:Farshad Farshad Khunjush] ('''2013'''). ''[https://scholar.google.de/citations?view_op=view_citation&hl=en&user=VvkRESgAAAAJ&citation_for_view=VvkRESgAAAAJ:ufrVoPGSRksC A parallel memetic algorithm on GPU to solve the task scheduling problem in heterogeneous environments]''. [http://www.sigevo.org/gecco-2013/program.html GECCO '13], [https://www.lri.fr/~hansen/proceedings/2013/GECCO/proceedings/p1181.pdf pdf]
 
* [[S. Ali Mirsoleimani]], [http://dblp.uni-trier.de/pers/hd/k/Karami:Ali Ali Karami], [http://dblp.uni-trier.de/pers/hd/k/Khunjush:Farshad Farshad Khunjush] ('''2013'''). ''[https://scholar.google.de/citations?view_op=view_citation&hl=en&user=VvkRESgAAAAJ&citation_for_view=VvkRESgAAAAJ:ufrVoPGSRksC A parallel memetic algorithm on GPU to solve the task scheduling problem in heterogeneous environments]''. [http://www.sigevo.org/gecco-2013/program.html GECCO '13], [https://www.lri.fr/~hansen/proceedings/2013/GECCO/proceedings/p1181.pdf pdf]
 +
* [[Ilya Loshchilov]]  ('''2013'''). ''[http://loshchilov.com/phd.html Surrogate-Assisted Evolutionary Algorithms]''. Ph.D. thesis, [[University of Paris#11|Paris-Sud 11 University]], advisors [[Marc Schoenauer]] and [[Michèle Sebag]]
 
'''2014'''
 
'''2014'''
 
* [[Eli David|Omid E. David]], [[Jaap van den Herik]], [[Moshe Koppel]], [[Nathan S. Netanyahu]] ('''2014'''). ''Genetic Algorithms for Evolving Computer Chess Programs''. [[IEEE#EC|IEEE Transactions on Evolutionary Computation]], [http://www.genetic-programming.org/hc2014/David-Paper.pdf pdf] <ref>[http://www.liacs.nl/nieuws/jaap-van-den-herik-wint-humies-award-2014/ Jaap van den Herik wint Humies Award 2014 - LIACS - Leiden Institute of Advanced Computer Science]</ref> <ref>[http://www.sigevo.org/gecco-2014/humies.html GECCO 2014]</ref>
 
* [[Eli David|Omid E. David]], [[Jaap van den Herik]], [[Moshe Koppel]], [[Nathan S. Netanyahu]] ('''2014'''). ''Genetic Algorithms for Evolving Computer Chess Programs''. [[IEEE#EC|IEEE Transactions on Evolutionary Computation]], [http://www.genetic-programming.org/hc2014/David-Paper.pdf pdf] <ref>[http://www.liacs.nl/nieuws/jaap-van-den-herik-wint-humies-award-2014/ Jaap van den Herik wint Humies Award 2014 - LIACS - Leiden Institute of Advanced Computer Science]</ref> <ref>[http://www.sigevo.org/gecco-2014/humies.html GECCO 2014]</ref>

Latest revision as of 10:17, 13 September 2019

Home * Learning * Genetic Programming

Genetic Programming [1]

Genetic Programming (GP),
an evolutionary based methodology inspired by biological evolution to optimize computer programs, in particular game playing programs. It is a machine learning technique used to optimize a population of programs, for instance to maximize the winning rate versus a set of opponents, after modifying evaluation weights or search parameter.

Evolutionary Programming

Evolutionary programming is similar to genetic programming, but the structure of the program to be optimized is fixed, while its numerical parameters are allowed to evolve. The term was coined by Lawrence J. Fogel in 1960.

Supersets

Genetic Programming is subset of a chain of subsequent fields in Artificial Intelligence.

Genetic Algorithms

Genetic Programming is a specialization of genetic algorithms (GA) where individuals are computer programs. This heuristic is routinely used to generate useful solutions to optimization and search problems. A genetic algorithm requires:

  1. Genetic representation
  2. Fitness function

performing the Genetic operations of

  1. Selection (genetic algorithm)
    1. Fitness proportionate selection
    2. Reward-based selection
    3. Stochastic universal sampling
    4. Tournament selection
    5. Truncation selection
  2. Crossover (genetic algorithm)

PBIL

Population-based incremental learning (PBIL) is a type of of genetic algorithm where the genotype of an entire population (probability vector) is evolved rather than individual members. The algorithm was proposed by Shumeet Baluja in 1994 [2]. The algorithm is simpler than a standard genetic algorithm, and in many cases leads to better results than a standard genetic algorithm [3].

Evolutionary Algorithms

Genetic algorithms belong to the larger class of evolutionary algorithms (EA). An EA uses some mechanisms inspired by biological evolution: reproduction, mutation, recombination, and selection. EAs are individual components that participate in an artificial evolution (AE).

Evolutionary Computation

An evolutionary algorithm (EA) is subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm. Evolutionary computation, introduced by John Henry Holland in the 1970s and more popular since 1990s mimics the population-based sexual evolution through reproduction of generations.

Computational Intelligence

Computational Intelligence (CI) is a set of Nature-inspired computational methodologies and approaches and field of Artificial Intelligence. It primarily includes many-valued logic or Fuzzy logic, Neural Networks, Evolutionary Computation, swarm intelligence and Artificial immune system.

See also

Publications

1950 ...

  • Nils Barricelli (1954). Esempi numerici di processi di evoluzione, Methodos, pp. 45-68, 1954
  • Nils Barricelli (1957). Symbiogenetic evolution processes realized by artificial methods. Methodos: 143–182.

1960 ...

1970 ...

  • John Henry Holland (1975). Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. amazon.com

1980 ...

1990 ...

1995 ...

2000 ....

2001

2002

2003

2004

2005 ...

2006

2007

2008

2009

2010 ...

2011

2012

2013

2014

2015 ...

Forum Posts

1996 ...

Re: Genetic Algorithms for Chess Evaluation Functions by Jay Scott, rgcc, July 01, 1996

2010 ...

2015 ...

Re: Genetical tuning by Ferdinand Mosca, CCC, August 20, 2015

External Links

Genetic Programming

Evolutionary Programming

Genetic Algorithms

Fitness proportionate selection from Wikipedia
Reward-based selection from Wikipedia
Stochastic universal sampling from Wikipedia
Tournament selection from Wikipedia
Truncation selection from Wikipedia

Evolutionary Algorithms

Evolutionary Computation

Misc

feat.: Bennie Maupin, Bill Summers, Paul Jackson, Mike Clark and Blackbird McKnight

References

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