Schütze, Oliver.

EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II [electronic resource] / edited by Oliver Schütze, Carlos A. Coello Coello, Alexandru-Adrian Tantar, Emilia Tantar, Pascal Bouvry, Pierre Del Moral, Pierrick Legrand. - Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013. - XXIV, 508 p. 152 illus. online resource. - Advances in Intelligent Systems and Computing, 175 2194-5357 ; . - Advances in Intelligent Systems and Computing, 175 .

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.

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. 


10.1007/978-3-642-31519-0 doi

Artificial intelligence.
Operations research.
Computational Intelligence.
Artificial Intelligence (incl. Robotics).
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
Mathematical Models of Cognitive Processes and Neural Networks.
Operation Research/Decision Theory.



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