Exploitation of Linkage Learning in Evolutionary Algorithms

One major branch of enhancing the performance of evolutionary algorithms is the exploitation of linkage learning. This monograph aims to capture the recent progress of linkage learning, by compiling a series of focused technical chapters to keep abreast of the developments and trends in the area of...

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Corporate Author: SpringerLink (Online service)
Other Authors: Chen, Ying-ping (Editor)
Format: eBook
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2010, 2010
Edition:1st ed. 2010
Series:Adaptation, Learning, and Optimization
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • Linkage and Problem Structures
  • Linkage Structure and Genetic Evolutionary Algorithms
  • Fragment as a Small Evidence of the Building Blocks Existence
  • Structure Learning and Optimisation in a Markov Network Based Estimation of Distribution Algorithm
  • DEUM – A Fully Multivariate EDA Based on Markov Networks
  • Model Building and Exploiting
  • Pairwise Interactions Induced Probabilistic Model Building
  • ClusterMI: Building Probabilistic Models Using Hierarchical Clustering and Mutual Information
  • Estimation of Distribution Algorithm Based on Copula Theory
  • Analyzing the k Most Probable Solutions in EDAs Based on Bayesian Networks
  • Applications
  • Protein Structure Prediction Based on HP Model Using an Improved Hybrid EDA
  • Sensible Initialization of a Computational Evolution System Using Expert Knowledge for Epistasis Analysis in Human Genetics
  • Estimating Optimal Stopping Rules in the Multiple Best Choice Problem with Minimal Summarized Rank via the Cross-Entropy Method