Improving Performance of GP by Adaptive Terminal Selection
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{ok00improving,
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author = "Sooyol Ok and Kazuo Miyashita and Seiichi Nishihara",
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title = "Improving Performance of {GP} by Adaptive Terminal
Selection",
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booktitle = "PRICAI 2000 Topics in Artificial Intelligence: 6th
Pacific Rim International Conference on Artificial
Intelligence",
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pages = "435--445",
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year = "2000",
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editor = "Riichiro Mizoguchi and John K. Slaney",
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series = "Lecture Notes in Artifical Intelligence",
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volume = "1886",
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address = "Melbourne Convention Centre, Austrlia",
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month = "28 " # aug # "-1 " # sep,
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "3-540-67925-1",
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bibsource = "DBLP, http://dblp.uni-trier.de",
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URL = "http://staff.aist.go.jp/k.miyashita/publications/PRICAI2000.ps",
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URL = "http://citeseer.ist.psu.edu/394599.html",
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abstract = "Genetic Programming (GP) is an evolutionary search
algorithm which searches a computer program capable of
producing the desired solution for a given problem. For
the purpose, it is necessary that GP system has access
to a set of features that are at least a superset of
the features necessary to solve the problem. However,
when the feature set given to GP is redundant, GP su
ers substantial loss of its eciency. This paper
presents a new approach in GP to acquire relevant
terminals from a redundant set of terminals. We propose
the adaptive mutation based on terminal weighting
mechanism for eliminating irrelevant terminals from the
redundant terminal set. We show empirically that the
proposed method is effective for finding relevant
terminals and improving performance of GP in the
experiments on symbolic regression problems.",
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notes = "PRICAI 2000 http://www3.cm.deakin.edu.au/pricai/
broken Mar 2021",
- }
Genetic Programming entries for
Sooyol Ok
Kazuo Miyashita
Seiichi Nishihara
Citations