A study on lamarckian and Baldwinian learning on noisy and noiseless landscapes

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1 Citation (Scopus)

Abstract

Lamarckian evolution and Baldwinian effect are two typical replacement schemes of the individual learning process in Memetic Computing. In this paper, we perform a comprehensive study on the behaviour of Lamarckian evolution and Baldwinian effect in noisy and noiseless continuous optimisation problems. The output of this comprehensive study shows that Lamarckian lifetime learning performs better on noiseless problem, while Baldwinian learning performs better on noisy problems.

Original languageEnglish
Title of host publicationProceedings - 24th European Conference on Modelling and Simulation, ECMS 2010
Pages323-329
Number of pages7
Publication statusPublished - 2010
Externally publishedYes
Event24th European Conference on Modelling and Simulation, ECMS 2010 - Kuala Lumpur, Malaysia
Duration: 1 Jun 20104 Jun 2010

Publication series

NameProceedings - 24th European Conference on Modelling and Simulation, ECMS 2010

Conference

Conference24th European Conference on Modelling and Simulation, ECMS 2010
Country/TerritoryMalaysia
CityKuala Lumpur
Period1/06/104/06/10

Free Keywords

  • Baldwinian effect
  • Lamarckian evolution
  • Landscape
  • Memetic computing
  • Optimisation

ASJC Scopus subject areas

  • Modelling and Simulation

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