Exploitation of Linkage Learning in Evolutionary Algorithms
Springer Berlin (Verlag)
978-3-642-12833-2 (ISBN)
Linkage and Problem Structures.- Linkage Structure and Genetic Evolutionary Algorithms.- Fragment as a Small Evidence of the Building Blocks Existence.- Structure Learning and Optimisation in a Markov Network Based Estimation of Distribution Algorithm.- DEUM - A Fully Multivariate EDA Based on Markov Networks.- Model Building and Exploiting.- Pairwise Interactions Induced Probabilistic Model Building.- ClusterMI: Building Probabilistic Models Using Hierarchical Clustering and Mutual Information.- Estimation of Distribution Algorithm Based on Copula Theory.- Analyzing the k Most Probable Solutions in EDAs Based on Bayesian Networks.- Applications.- Protein Structure Prediction Based on HP Model Using an Improved Hybrid EDA.- Sensible Initialization of a Computational Evolution System Using Expert Knowledge for Epistasis Analysis in Human Genetics.- Estimating Optimal Stopping Rules in the Multiple Best Choice Problem with Minimal Summarized Rank via the Cross-Entropy Method.
Erscheint lt. Verlag | 3.5.2010 |
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Reihe/Serie | Adaptation, Learning, and Optimization |
Zusatzinfo | X, 246 p. 30 illus. in color. |
Verlagsort | Berlin |
Sprache | englisch |
Maße | 155 x 235 mm |
Gewicht | 610 g |
Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
Technik | |
Schlagworte | algorithm • algorithms • Bayesian Network • Calculus • Evolution • Evolutionäre Algorithmen • evolutionary algorithm • evolutionary computation • Genetics • Knowledge • learning • Linkage Learning • Markov • Model • Optimization |
ISBN-10 | 3-642-12833-5 / 3642128335 |
ISBN-13 | 978-3-642-12833-2 / 9783642128332 |
Zustand | Neuware |
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