LEADER 04509nam 22008415 450 001 9910438049503321 005 20251230061900.0 010 $a9786613943835 010 $a9781283631389 010 $a1283631385 010 $a9783642315190 010 $a3642315194 024 7 $a10.1007/978-3-642-31519-0 035 $a(CKB)2560000000090998 035 $a(EBL)994703 035 $a(OCoLC)808366763 035 $a(SSID)ssj0000745950 035 $a(PQKBManifestationID)11412852 035 $a(PQKBTitleCode)TC0000745950 035 $a(PQKBWorkID)10863123 035 $a(PQKB)11568594 035 $a(DE-He213)978-3-642-31519-0 035 $a(MiAaPQ)EBC994703 035 $a(PPN)168319594 035 $a(EXLCZ)992560000000090998 100 $a20120813d2013 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aEVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II /$fedited by Oliver Schütze, Carlos A. Coello Coello, Alexandru-Adrian Tantar, Emilia Tantar, Pascal Bouvry, Pierre Del Moral, Pierrick Legrand 205 $a1st ed. 2013. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2013. 215 $a1 online resource (503 p.) 225 1 $aAdvances in Intelligent Systems and Computing,$x2194-5365 ;$v175 300 $aInternational conference proceedings. 311 08$a9783642315183 311 08$a3642315186 320 $aIncludes bibliographical references and index. 327 $aPart 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. 330 $aThis book comprises a selection of papers from the EVOLVE 2012 held in Mexico City, Mexico. The aim of the EVOLVE is to build a bridge between probability, set oriented numerics and evolutionary computing, as to identify new common and challenging research aspects. The conference is also intended to foster a growing interest for robust and efficient methods with a sound theoretical background. EVOLVE is intended to unify theory-inspired methods and cutting-edge techniques ensuring performance guarantee factors. By gathering researchers with different backgrounds, a unified view and vocabulary can emerge where the theoretical advancements may echo in different domains. Summarizing, the EVOLVE focuses on challenging aspects arising at the passage from theory to new paradigms and aims to provide a unified view while raising questions related to reliability,  performance guarantees and modeling. The papers of the EVOLVE 2012 make a contribution to this goal. . 410 0$aAdvances in Intelligent Systems and Computing,$x2194-5365 ;$v175 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aStatistics 606 $aNeural networks (Computer science) 606 $aOperations research 606 $aComputational Intelligence 606 $aArtificial Intelligence 606 $aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences 606 $aMathematical Models of Cognitive Processes and Neural Networks 606 $aOperations Research and Decision Theory 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 0$aStatistics. 615 0$aNeural networks (Computer science). 615 0$aOperations research. 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 615 24$aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences. 615 24$aMathematical Models of Cognitive Processes and Neural Networks. 615 24$aOperations Research and Decision Theory. 676 $a006.30151 676 $a519.02/462 701 $aSchutze$b Oliver$01222824 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910438049503321 996 $aEVOLVE-- A bridge between probability, set oriented numerics and evolutionary computation$94191432 997 $aUNINA