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024 7 $a10.1007/978-3-642-32726-1
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100   $a20120920d2013      uy         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt
182   $cc
183   $acr
200 00$aEVOLVE $ea bridge between probability, set oriented numerics and evolutionary computation /$fEmilia Tantar ... [et al.] (eds.)
205   $a1st ed. 2013.
210   $aBerlin ;$aNew York $cSpringer$dc2013
215   $a1 online resource (XXII, 414 p.) 
225 1 $aStudies in computational intelligence ;$v447
300   $aInternational conference proceedings.
311   $a3-642-44503-9 
311   $a3-642-32725-7 
320   $aIncludes bibliographical references.
327   $aPart I Foundations, probability and evolutionary computation -- Part II Set oriented numerics -- Part III Landscape, coevolution and cooperation -- Part IV Multi-objective optimization, heuristic conversion algorithms.
330   $aThe aim of this book is to provide a strong theoretical support for understanding and analyzing the behavior of evolutionary algorithms, as well as for creating a bridge between probability, set-oriented numerics and evolutionary computation. The volume encloses a collection of contributions that were presented at the EVOLVE 2011 international workshop, held in Luxembourg, May 25-27, 2011, coming from invited speakers and also from selected regular submissions. The aim of EVOLVE is to unify the perspectives offered by probability, set oriented numerics and evolutionary computation. EVOLVE focuses on challenging aspects that arise at the passage from theory to new paradigms and practice, elaborating on the foundations of evolutionary algorithms and theory-inspired methods merged with cutting-edge techniques that ensure performance guarantee factors. EVOLVE is also intended to foster a growing interest for robust and efficient methods with a sound theoretical background. The chapters enclose challenging theoretical findings, concrete optimization problems as well as new perspectives. By gathering contributions from researchers with different backgrounds, the book is expected to set the basis for a unified view and vocabulary where theoretical advancements may echo in different domains.
410  0$aStudies in computational intelligence ;$vv. 447.
606   $aEvolutionary computation$vCongresses
606   $aGenetic programming (Computer science)$vCongresses
615  0$aEvolutionary computation
615  0$aGenetic programming (Computer science)
676   $a006.3
701   $aTantar$b Emilia$01756397
712 12$aEVOLVE 2011
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910438056003321
996   $aEVOLVE$94193653
997   $aUNINA