EVOLVE-- a bridge between probability, set oriented numerics, and evolutionary computation III [electronic resource] / Oliver Schütze [and 6 more] (eds.).
2013
QA76.618 .E96 2013
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Title
EVOLVE-- a bridge between probability, set oriented numerics, and evolutionary computation III [electronic resource] / Oliver Schütze [and 6 more] (eds.).
ISBN
9783319014609 electronic book
3319014609 electronic book
9783319014593
3319014609 electronic book
9783319014593
Published
Cham : Springer, [2013]
Copyright
©2014
Language
English
Description
1 online resource (xviii, 261 pages) : illustrations.
Item Number
10.1007/978-3-319-01460-9 doi
Call Number
QA76.618 .E96 2013
Dewey Decimal Classification
006.3
Summary
This book comprises a selection of extended abstracts and papers presented at 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 computation 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 aims 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 conference 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 extended papers of the EVOLVE 2012 make a contribution to this goal.
Note
Includes author index.
Access Note
Access limited to authorized users.
Source of Description
Description based on online resource; title from PDF title page (SpringerLink, viewed August 20, 2013).
Added Meeting Name
Series
Studies in computational intelligence ; v.500.
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Table of Contents
Probabilistic Modeling
Evolutionary Computation for Vision, Graphics, and Robotics
Multi-objective Optimization.
Evolutionary Computation for Vision, Graphics, and Robotics
Multi-objective Optimization.