Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
The sciences of the artificial (3rd ed.)
The sciences of the artificial (3rd ed.)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
A Survey of Optimization by Building and Using Probabilistic Models
Computational Optimization and Applications
Using Optimal Dependency-Trees for Combinational Optimization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Finding Multimodal Solutions Using Restricted Tournament Selection
Proceedings of the 6th International Conference on Genetic Algorithms
From Recombination of Genes to the Estimation of Distributions I. Binary Parameters
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Linkage learning, overlapping building blocks, and systematic strategy for scalable recombination
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Does overfitting affect performance in estimation of distribution algorithms
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Analyzing probabilistic models in hierarchical BOA on traps and spin glasses
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Population sizing for entropy-based model building in discrete estimation of distribution algorithms
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Predictive models for the breeder genetic algorithm i. continuous parameter optimization
Evolutionary Computation
The gambler's ruin problem, genetic algorithms, and the sizing of populations
Evolutionary Computation
Scalability problems of simple genetic algorithms
Evolutionary Computation
From mating pool distributions to model overfitting
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Substructural neighborhoods for local search in the bayesian optimization algorithm
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Hierarchical allelic pairwise independent functions
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Influence of selection on structure learning in markov network EDAs: an empirical study
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Linkage neighbors, optimal mixing and forced improvements in genetic algorithms
Proceedings of the 14th annual conference on Genetic and evolutionary computation
A niching scheme for EDAs to reduce spurious dependencies
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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Numerous studies have shown that advanced estimation of distribution algorithms (EDAs) often discover spurious (unnecessary) dependencies. Nonetheless, only little prior work exists that would study the effects of spurious dependencies on EDA performance. This paper examines the effects of spurious dependencies on the performance and scalability of EDAs with the main focus on EDAs with marginal product models and the onemax problem. A theoretical model is proposed to analyze the effects of spurious dependencies on the population sizing in EDAs and the theory is verified with experiments. The effects of spurious dependencies on the number of generations are studied empirically. The effects of replacement strategies on the performance of EDAs with spurious linkage are also investigated.