LEARNABLE EVOLUTION MODEL: Evolutionary Processes Guided by Machine Learning
Machine Learning - Special issue on multistrategy learning
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
A Survey of Optimization by Building and Using Probabilistic Models
Computational Optimization and Applications
The Proportional Genetic Algorithm: Gene Expression in a Genetic Algorithm
Genetic Programming and Evolvable Machines
Spin-flip symmetry and synchronization
Evolutionary Computation
Modeling Building-Block Interdependency
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
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
Genetic Algorithms Using Grammatical Evolution
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On the importance of diversity maintenance in estimation of distribution algorithms
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
A theoretical analysis of the HIFF problem
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Statistics for Business and Economics (with Student CD-ROM, iPod Key Term, and InfoTrac )
Statistics for Business and Economics (with Student CD-ROM, iPod Key Term, and InfoTrac )
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Proceedings of the 9th annual conference on Genetic and evolutionary computation
Maintaining Diversity in EDAs for Real-Valued Optimisation Problems
FBIT '07 Proceedings of the 2007 Frontiers in the Convergence of Bioscience and Information Technologies
Representation development from pareto-coevolution
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Wise breeding GA via machine learning techniques for function optimization
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Building classifiers using Bayesian networks
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Diversity loss in general estimation of distribution algorithms
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Candidate oversampling prefers two to tango: estimation of distribution algorithms
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
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Evolutionary Algorithms based on Probabilistic Modeling is a growing research field. Recently, hybrids that borrow ideas from the field of classification were introduced. We extend such hybrids, and evaluate four strategies for truncation of an over-sized population of samples. The strategies are evaluated over a number of difficult problems from the literature, among them, a hierarchical 256-bit HIFF problem. We show that over-sampling in conjunction with a truncation strategy can guide the search without increasing the number of performed fitness evaluations per generation, and that a truncation strategy which inverses the sampling pressure can, fitness-wise, perform significantly better than regular sampling.