A connectionist machine for genetic hillclimbing
A connectionist machine for genetic hillclimbing
Management Science
Global optimization
Semi-naive Bayesian classifier
EWSL-91 Proceedings of the European working session on learning on Machine learning
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Elements of information theory
Elements of information theory
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Machine Learning - Special issue on learning with probabilistic representations
LEARNABLE EVOLUTION MODEL: Evolutionary Processes Guided by Machine Learning
Machine Learning - Special issue on multistrategy learning
Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Schemata, Distributions and Graphical Models in Evolutionary Optimization
Journal of Heuristics
Extending Population-Based Incremental Learning to Continuous Search Spaces
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
Towards a New Evolutionary Computation: Advances on Estimation of Distribution Algorithms (Studies in Fuzziness and Soft Computing)
Wise breeding GA via machine learning techniques for function optimization
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Evolutionary bayesian classifier-based optimization in continuous domains
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
Stochastic Local Search Techniques with Unimodal Continuous Distributions: A Survey
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Multi-objective combinatorial optimisation with coincidence algorithm
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
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This paper introduces a evolutionary computation method that applies Bayesian classifiers to optimization problems. This approach is based on Estimation of Distribution Algorithms (EDAs) in which Bayesian or Gaussian networks are applied to the evolution of a population of individuals (i.e. potential solutions to the optimization problem) in order to improve the quality of the individuals of the next generation. Our new approach, called Evolutionary Bayesian Classifier-based Optimization Algorithm (EBCOA), employs Bayesian classifiers instead of Bayesian or Gaussian networks in order to evolve individuals to a fitter population. In brief, EBCOAs are characterized by applying Bayesian classification techniques-usually applied to supervised classification problems-to optimization in continuous domains. We propose and review in this paper different Bayesian classifiers for implementing our EBCOA method, focusing particularly on EBCOAs applying naïve Bayes, semi-na¨ive Bayes, and tree augmented na¨ive Bayes classifiers. This work presents a deep study on the behavior of these algorithms with classical optimiztion problems in continuous domains. The different parameters used for tuning the performance of the algorithms are discussed, and a comprehensive overview of their influence is provided. We also present experimental results to compare this new method with other state of the art approaches of the evolutionary computation field for continuous domains such as Evolutionary Strategies (ES) and Estimation of Distribution Algorithms (EDAs).