Convergence Theorems of Estimation of Distribution Algorithms

DOI10.1007/978-3-642-28900-2_6zbMath1251.68212OpenAlexW2185396837MaRDI QIDQ4649192

Heinz Mühlenbein

Publication date: 20 November 2012

Published in: Adaptation, Learning, and Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-642-28900-2_6

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Graph theory (including graph drawing) in computer science (68R10) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20) Graphical methods in statistics (62A09)

Related Items (3)

A Boltzmann based estimation of distribution algorithm ⋮ A review of message passing algorithms in estimation of distribution algorithms ⋮ A factor graph based genetic algorithm

Cites Work

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• MARLEDA: effective distribution estimation through Markov random fields
• An introduction to MCMC for machine learning
• Evolutionary optimization and the estimation of search distributions with applications to graph bipartitioning.
• Schemata, distributions and graphical models in evolutionary optimization
• Bounding the convergence time of the Gibbs sampler in Bayesian image restoration
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Factor graphs and the sum-product algorithm

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