LEADER 05638nam 22007815 450 001 996465302203316 005 20200702124848.0 010 $a3-540-45322-9 024 7 $a10.1007/3-540-45322-9 035 $a(CKB)1000000000211669 035 $a(SSID)ssj0000326924 035 $a(PQKBManifestationID)11232111 035 $a(PQKBTitleCode)TC0000326924 035 $a(PQKBWorkID)10298380 035 $a(PQKB)10446992 035 $a(DE-He213)978-3-540-45322-2 035 $a(MiAaPQ)EBC3071990 035 $a(PPN)15520078X 035 $a(EXLCZ)991000000000211669 100 $a20121227d2001 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aStochastic Algorithms: Foundations and Applications$b[electronic resource] $eInternational Symposium, SAGA 2001 Berlin, Germany, December 13-14, 2001 Proceedings /$fedited by Kathleen Steinhöfel 205 $a1st ed. 2001. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2001. 215 $a1 online resource (CCXVI, 208 p.) 225 1 $aLecture Notes in Computer Science,$x0302-9743 ;$v2264 300 $aIncludes index. 311 $a3-540-43025-3 327 $aRandomized Communication Protocols -- Optimal Mutation Rate Using Bayesian Priors for Estimation of Distribution Algorithms -- An Experimental Assessment of a Stochastic, Anytime, Decentralized, Soft Colourer for Sparse Graphs -- Randomized Branching Programs -- Yet Another Local Search Method for Constraint Solving -- An Evolutionary Algorithm for the Sequence Coordination in Furniture Production -- Evolutionary Search for Smooth Maps in Motor Control Unit Calibration -- Some Notes on Random Satisfiability -- Prospects for Simulated Annealing Algorithms in Automatic Differentiation -- Optimization and Simulation: Sequential Packing of Flexible Objects Using Evolutionary Algorithms -- Stochastic Finite Learning -- Sequential Sampling Algorithms: Unified Analysis and Lower Bounds -- Approximate Location of Relevant Variables under the Crossover Distribution. 330 $aSAGA 2001, the ?rst Symposium on Stochastic Algorithms, Foundations and Applications, took place on December 13?14, 2001 in Berlin, Germany. The present volume comprises contributed papers and four invited talks that were included in the ?nal program of the symposium. Stochastic algorithms constitute a general approach to ?nding approximate solutions to a wide variety of problems. Although there is no formal proof that stochastic algorithms perform better than deterministic ones, there is evidence by empirical observations that stochastic algorithms produce for a broad range of applications near-optimal solutions in a reasonable run-time. The symposium aims to provide a forum for presentation of original research in the design and analysis, experimental evaluation, and real-world application of stochastic algorithms. It focuses, in particular, on new algorithmic ideas invo- ing stochastic decisions and exploiting probabilistic properties of the underlying problem domain. The program of the symposium re?ects the e?ort to promote cooperation among practitioners and theoreticians and among algorithmic and complexity researchers of the ?eld. In this context, we would like to express our special gratitude to DaimlerChrysler AG for supporting SAGA 2001. The contributed papers included in the proceedings present results in the following areas: Network and distributed algorithms; local search methods for combinatorial optimization with application to constraint satisfaction problems, manufacturing systems, motor control unit calibration, and packing ?exible - jects; and computational learning theory. 410 0$aLecture Notes in Computer Science,$x0302-9743 ;$v2264 606 $aProbabilities 606 $aAlgorithms 606 $aComputers 606 $aComputer science?Mathematics 606 $aCombinatorics 606 $aMathematical statistics 606 $aProbability Theory and Stochastic Processes$3https://scigraph.springernature.com/ontologies/product-market-codes/M27004 606 $aAlgorithm Analysis and Problem Complexity$3https://scigraph.springernature.com/ontologies/product-market-codes/I16021 606 $aComputation by Abstract Devices$3https://scigraph.springernature.com/ontologies/product-market-codes/I16013 606 $aDiscrete Mathematics in Computer Science$3https://scigraph.springernature.com/ontologies/product-market-codes/I17028 606 $aCombinatorics$3https://scigraph.springernature.com/ontologies/product-market-codes/M29010 606 $aProbability and Statistics in Computer Science$3https://scigraph.springernature.com/ontologies/product-market-codes/I17036 615 0$aProbabilities. 615 0$aAlgorithms. 615 0$aComputers. 615 0$aComputer science?Mathematics. 615 0$aCombinatorics. 615 0$aMathematical statistics. 615 14$aProbability Theory and Stochastic Processes. 615 24$aAlgorithm Analysis and Problem Complexity. 615 24$aComputation by Abstract Devices. 615 24$aDiscrete Mathematics in Computer Science. 615 24$aCombinatorics. 615 24$aProbability and Statistics in Computer Science. 676 $a519.23 702 $aSteinhöfel$b Kathleen$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996465302203316 996 $aStochastic Algorithms: Foundations and Applications$9772662 997 $aUNISA