EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II

2013
ISBN: 978-3-642-31518-3
Verlag: Springer

Buch, Englisch, Band 175, 508 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 797 g

Reihe: Advances in Intelligent Systems and Computing

This book comprises a selection of papers from the EVOLVE 2012 held in Mexico City, Mexico. The aim of the EVOLVE is to build a bridge between probability, set oriented numerics and evolutionary computing, as to identify new common and challenging research aspects.
The conference is also intended to foster a growing interest for robust and efficient methods with a sound theoretical background. EVOLVE is intended to unify theory-inspired methods and cutting-edge techniques ensuring performance guarantee factors. By gathering researchers with different backgrounds, a unified view and vocabulary can emerge where the theoretical advancements
may echo in different domains. Summarizing, the EVOLVE focuses on challenging aspects arising at the passage from theory to new paradigms and aims to provide a unified view while raising questions related to reliability,  performance guarantees and modeling. The papers of the EVOLVE 2012 make a contribution to this goal.

Zielgruppe

Research

Autoren/Hrsg.

Schütze, Oliver

Coello Coello, Carlos A.

Tantar, Alexandru-Adrian

Legrand, Pierrick

Tantar, Emilia

Bouvry, Pascal

Del Moral, Pierre

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik

Inhaltsverzeichnis

Part I Cell Mapping and Quasi-stationary Distributions.- Part II Genetic Programming.- Part III EvolutionaryMulti-objective Optimization.- Part IV Combinatorial Optimization.- Part V ProbabilisticModeling and Optimization for Emerging Networks.- Part VI Hybrid Probabilistic Models for Real Parameter Optimization and their Applications.- Part VII Evolutionary Computation for Vision, Graphics, and Robotics.- Part VIII Real-world Application of Bio-inspired Metaheuristics.