| 書(shū)目名稱 | Estimation of Distribution Algorithms |
| 副標(biāo)題 | A New Tool for Evolu |
| 編輯 | Pedro Larra?aga,Jose A. Lozano |
| 視頻video | http://file.papertrans.cn/316/315787/315787.mp4 |
| 叢書(shū)名稱 | Genetic Algorithms and Evolutionary Computation |
| 圖書(shū)封面 |  |
| 描述 | .Estimation of Distribution Algorithms: A New Tool forEvolutionary. .Computation. is devoted to a new paradigm forevolutionary computation, named estimation of distribution algorithms(EDAs). This new class of algorithms generalizes genetic algorithms byreplacing the crossover and mutation operators with learning andsampling from the probability distribution of the best individuals ofthe population at each iteration of the algorithm. Working in such away, the relationships between the variables involved in the problemdomain are explicitly and effectively captured and exploited. .This text constitutes the first compilation and review of thetechniques and applications of this new tool for performingevolutionary computation. .Estimation of Distribution Algorithms: ANew. .Tool for Evolutionary Computation. is clearly divided intothree parts. Part I is dedicated to the foundations of EDAs. In thispart, after introducing some probabilistic graphical models -Bayesian and Gaussian networks - a review of existing EDAapproaches is presented, as well as some new methods based on moreflexible probabilistic graphical models. A mathematical modeling ofdiscrete EDAs is also presented. Part II cove |
| 出版日期 | Book 2002 |
| 關(guān)鍵詞 | Bayesian network; Cluster; algorithms; evolutionary algorithm; genetic algorithms; k-means; learning; machi |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4615-1539-5 |
| isbn_softcover | 978-1-4613-5604-2 |
| isbn_ebook | 978-1-4615-1539-5Series ISSN 1568-2587 |
| issn_series | 1568-2587 |
| copyright | Springer Science+Business Media New York 2002 |
|Archiver|手機(jī)版|小黑屋|
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