Results 241 to 250 of about 1,087,874 (283)

Space Complexity of Estimation of Distribution Algorithms

Evolutionary Computation, 2005
In this paper, we investigate the space complexity of the Estimation of Distribution Algorithms (EDAs), a class of sampling-based variants of the genetic algorithm. By analyzing the nature of EDAs, we identify criteria that characterize the space complexity of two typical implementation schemes of EDAs, the factorized distribution algorithm and ...
Yong, Gao, Joseph, Culberson
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Unbiasedness of estimation-of-distribution algorithms

Theoretical Computer Science, 2019
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Tobias Friedrich, Timo Kötzing, Martin S. Krejca   +2 more
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Estimation of Distribution Algorithms

2016
Estimation of distribution algorithm (EDA) is a most successful paradigm of EAs. EDAs are derived by inspirations from evolutionary computation and machine learning. This chapter describes EDAs as well as several classical EDA implementations.
Ke-Lin Du, M. N. S. Swamy
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Estimation of Distribution Algorithms

2015
Estimation of distribution algorithms (EDA s) guide the search for the optimum by building and sampling explicit probabilistic models of promising candidate solutions. However, EDAs are not only optimization techniques; besides the optimum or its approximation, EDAs provide practitioners with a series of probabilistic models that reveal a lot of ...
Martin Pelikan, Mark W. Hauschild, Fernando G. Lobo   +2 more
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Subspace estimation of distribution algorithms: To perturb part of all variables in estimation of distribution algorithms

Applied Soft Computing, 2011
Abstract: In the traditional estimation of distribution algorithms (EDAs), all the variables of candidate individuals are perturbed through sampling from a probability distribution of promising individuals. However, it may be unnecessary for the EDAs to perturb all variables of candidate individuals at each generation.
Helong Li, Yi Hong, Sam Kwong
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Estimation of distribution algorithms

Proceedings of the 13th annual conference companion on Genetic and evolutionary computation, 2011
This paper focuses on the analysis of estimation of distribution algorithms (EDAs) software. The important role played by EDAs implementations in the usability and range of applications of these algorithms is considered. A survey of available EDA software is presented, and classifications based on the class of programming languages and design ...
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Estimation of Distribution Algorithms

2006
Training Artificial Neural Networks (ANNs) is a very complex task with a high practical relevance in the field of supervised learning. In this chapter, the problem of training ANNs is faced with several Estimation of Distribution Algorithms (EDAs) with different features, exploring both continuous and discrete search spaces. These EDAs have been tested
Julio Madera, Bernabé Dorronsoro
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Estimation of Distribution Algorithms with Kikuchi Approximations

Evolutionary Computation, 2005
The question of finding feasible ways for estimating probability distributions is one of the main challenges for Estimation of Distribution Algorithms (EDAs). To estimate the distribution of the selected solutions, EDAs use factorizations constructed according to graphical models. The class of factorizations that can be obtained from these probability
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Pair-copula estimation of distribution algorithms

International Journal of Computing Science and Mathematics, 2013
Summary: Copula theory provides a promising solution for the estimation of population probability in estimation distribution algorithms (EDAs), and more and more researchers pay attention to copula-EDAs. Most of the copula-EDAs researches are related to two variables case, in this paper, by taking advantage of the ability of pair-copula in high ...
Gao, Huimin, Wang, Xiaoping
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