Grammar-based genetic programming with dependence learning and Bayesian network classifier

Pak Kan WONG, Leung Yau LO, Man Leung WONG, Kwong Sak LEUNG

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

4 Citations (Scopus)

Abstract

Grammar-Based Genetic Programming formalizes constraints on the solution structure based on domain knowledge to reduce the search space and generate grammatically correct individuals. Nevertheless, building blocks in a program can often be dependent, so the effective search space can be further reduced. Approaches have been proposed to learn the dependence using probabilistic models and shown to be useful in finding the optimal solutions with complex structure. It raises questions on how to use the individuals in the population to uncover the underlying dependence. Usually, only the good individuals are selected. To model the dependence better, we introduce Grammar-Based Genetic Programming with Bayesian Network Classifier (GBGPBC) which also uses poorer individuals. With the introduction of class labels, we further propose a refinement technique on probability distribution based on class label. Our results show that GBGPBC performs well on two benchmark problems. These techniques boost the performance of our system.
Original languageEnglish
Title of host publicationGECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference
PublisherAssociation for Computing Machinery
Pages959-966
Number of pages8
ISBN (Print)9781450326629
DOIs
Publication statusPublished - 12 Jul 2014

Fingerprint

Genetic programming
Bayesian networks
Classifiers
Labels
Probability distributions

Bibliographical note

Paper presented at the 16th Genetic and Evolutionary Computation Conference (GECCO), Jul 12-16, 2014, Vancouver, Canada.

Keywords

  • Bayesian network
  • Classifier
  • Genetic programming
  • Grammar-based genetic programming

Cite this

WONG, P. K., LO, L. Y., WONG, M. L., & LEUNG, K. S. (2014). Grammar-based genetic programming with dependence learning and Bayesian network classifier. In GECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference (pp. 959-966). Association for Computing Machinery. https://doi.org/10.1145/2576768.2598256
WONG, Pak Kan ; LO, Leung Yau ; WONG, Man Leung ; LEUNG, Kwong Sak. / Grammar-based genetic programming with dependence learning and Bayesian network classifier. GECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference. Association for Computing Machinery, 2014. pp. 959-966
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WONG, PK, LO, LY, WONG, ML & LEUNG, KS 2014, Grammar-based genetic programming with dependence learning and Bayesian network classifier. in GECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference. Association for Computing Machinery, pp. 959-966. https://doi.org/10.1145/2576768.2598256

Grammar-based genetic programming with dependence learning and Bayesian network classifier. / WONG, Pak Kan; LO, Leung Yau; WONG, Man Leung; LEUNG, Kwong Sak.

GECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference. Association for Computing Machinery, 2014. p. 959-966.

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

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WONG PK, LO LY, WONG ML, LEUNG KS. Grammar-based genetic programming with dependence learning and Bayesian network classifier. In GECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference. Association for Computing Machinery. 2014. p. 959-966 https://doi.org/10.1145/2576768.2598256