LEADER 05566nam 22007455 450 001 996465755803316 005 20200706020926.0 010 $a3-540-69538-9 024 7 $a10.1007/BFb0028514 035 $a(CKB)1000000000234701 035 $a(SSID)ssj0000326655 035 $a(PQKBManifestationID)11912765 035 $a(PQKBTitleCode)TC0000326655 035 $a(PQKBWorkID)10312640 035 $a(PQKB)10847043 035 $a(DE-He213)978-3-540-69538-7 035 $a(PPN)155226622 035 $a(EXLCZ)991000000000234701 100 $a20121227d1997 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aSimulated Evolution and Learning$b[electronic resource] $eFirst Asia-Pacific Conference, SEAL'96, Taejon, Korea, November 9-12, 1996. Selected Papers. /$fedited by Xin Yao, Jong-Hwan Kim, Takeshi Furuhashi 205 $a1st ed. 1997. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d1997. 215 $a1 online resource (X, 238 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v1285 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-63399-5 327 $aEmergent phenomena and computer worlds -- Top-down evolutionary engineering -- Function optimization using evolutionary programming with self-adaptive cultural algorithms -- An adaptive evolutionary algorithm for numerical optimization -- Lagrangian-based evolutionary programming for constrained optimization -- Selection of input variables of fuzzy model using genetic algorithm with quick fuzzy inference -- Entropic sampling in genetic-entropic algorithm -- Computational and learning synergies with a coevolving multilevel architecture -- Evolving state and memory in genetic programming -- Evolutionary CT image reconstruction by image partitioning -- Genetic learning of the irrigation cycle for water flow in cropped soils -- Optimization of parameters of color image segmentation using evolutionary programming -- Genetic algorithms for solving multiprocessor scheduling problems -- A study on co-evolutionary learning of neural networks -- Knowledge acquisition of fuzzy control rules for mobile robots using DNA coding method and pseudo-bacterial GA -- Evolutionary learning algorithm for projection neural networks -- EPNet for chaotic time-series prediction -- Would and should government lie about economic statistics: simulations based o evolutionary cellular automata -- A technique for improving the convergence characteristic of genetic algorithms and its application to a genetic-based load flow algorithm -- Knowledge extraction using neural network by an artificial life approach -- An inference method using multiple patterns and modification of pattern space -- Random search based on genetic operators -- Hybrid evolutionary learning of fuzzy logic and genetic algorithm -- Fuzzy identification of unknown systems based on GA -- Competitive co-evolution model on the acquisition of game strategy. 330 $aThis book constitutes the thoroughly refereed post-conference documentation of the First Asia-Pacific Conference on Simulated Evolution and Learning, SEAL'96, held in Taejon, Korea, in November 1996. The 23 revised full papers were selected for inclusion in this book on the basis of 2 rounds of reviewing and improvements. Also included are invited papers by John L. Casti and Lawrence J. Fogel. The volume covers a wide range of current topics in simulated evolution and learning e.g. evolutionary optimization, evolutionary learning, artificial life, hybrid evolutionary fuzzy systems, evolutionary artificial neural networks, co-evolution, novel evolutionary approaches to computer tomography image reconstruction, power systems load flow control, and water flow control in cropped soils. 410 0$aLecture Notes in Artificial Intelligence ;$v1285 606 $aArtificial intelligence 606 $aComputer simulation 606 $aComputers 606 $aBioinformatics  606 $aComputational biology  606 $aComputational complexity 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aSimulation and Modeling$3https://scigraph.springernature.com/ontologies/product-market-codes/I19000 606 $aComputation by Abstract Devices$3https://scigraph.springernature.com/ontologies/product-market-codes/I16013 606 $aComputer Appl. in Life Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/L17004 606 $aComplexity$3https://scigraph.springernature.com/ontologies/product-market-codes/T11022 615 0$aArtificial intelligence. 615 0$aComputer simulation. 615 0$aComputers. 615 0$aBioinformatics . 615 0$aComputational biology . 615 0$aComputational complexity. 615 14$aArtificial Intelligence. 615 24$aSimulation and Modeling. 615 24$aComputation by Abstract Devices. 615 24$aComputer Appl. in Life Sciences. 615 24$aComplexity. 676 $a006.3 702 $aYao$b Xin$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aKim$b Jong-Hwan$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aFuruhashi$b Takeshi$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 12$aSEAL '96 906 $aBOOK 912 $a996465755803316 996 $aSimulated Evolution and Learning$9772256 997 $aUNISA