EVOLVE – A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation VII  [electronic resource] / 
edited by Michael Emmerich, André Deutz, Oliver Schütze, Pierrick Legrand, Emilia Tantar, Alexandru-Adrian Tantar. 
 - 1st ed. 2017. 
 - VIII, 210 p. 75 illus., 36 illus. in color.  online resource. 
 - Studies in Computational Intelligence,  662  1860-9503 ; .
 - Studies in Computational Intelligence,  662 .
<br/><br/>A Survey of Diversity Oriented Optimization: Problems, Indicators, and Algorithms -- Global Multi-Objective Optimization by Means of Cell Mapping Techniques -- Percentile via Polynomial Chaos Expansion: Bridging Robust Optimization with Reliability -- Evolutionary Equilibrium Detection in Multicriteria Games -- A New Estimation of Distribution Algorithm for Nash Equilibria Detection -- Multi-Objective Optimisation by Self-Adaptive Evolutionary Algorithm -- Evidence Based Multidisciplinary Robust Optimization for Mars Micro Entry Probe Design -- A Simulation-Based Algorithm for the Probabilistic Traveling Salesman Problem -- Average Cuboid Volume as a Convergence Indicator and Selection Criterion for Multi-Objective Biochemical Optimization. 
<br/><br/> This book comprises nine selected works on numerical and computational methods for solving multiobjective optimization, game theory, and machine learning problems. It provides extended versions of selected papers from various fields of science such as computer science, mathematics and engineering that were presented at EVOLVE 2013 held in July 2013 at Leiden University in the Netherlands. The internationally peer-reviewed papers include original work on important topics in both theory and applications, such as the role of diversity in optimization, statistical approaches to combinatorial optimization, computational game theory, and cell mapping techniques for numerical landscape exploration. Applications focus on aspects including robustness, handling multiple objectives, and complex search spaces in engineering design and computational biology. 
<br/><br/><label>ISBN: </label>9783319493251 
<br/><br/><label>Standard No.: </label>10.1007/978-3-319-49325-1  doi 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Computational intelligence.<br/>Artificial intelligence.<br/>Probabilities.<br/>Computer science—Mathematics.<br/>Mathematics—Data processing.<br/>Computational Intelligence.<br/>Artificial Intelligence.<br/>Probability Theory.<br/>Mathematics of Computing.<br/>Computational Mathematics and Numerical Analysis.
<br/><br/><label>LC Class. No.: </label>Q342 
<br/><br/><label>Dewey Class. No.: </label>006.3