LEADER 05441nam 22007695 450 001 996466145803316 005 20200701183542.0 010 $a3-540-48999-1 024 7 $a10.1007/3-540-58483-8 035 $a(CKB)1000000000234188 035 $a(SSID)ssj0000323011 035 $a(PQKBManifestationID)11937887 035 $a(PQKBTitleCode)TC0000323011 035 $a(PQKBWorkID)10289654 035 $a(PQKB)11125342 035 $a(DE-He213)978-3-540-48999-3 035 $a(PPN)155207830 035 $a(EXLCZ)991000000000234188 100 $a20121227d1994 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aEvolutionary Computing$b[electronic resource] $eAISB Workshop, Leeds, U.K., April 11 - 13, 1994. Selected Papers /$fedited by Terence C. Fogarty 205 $a1st ed. 1994. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d1994. 215 $a1 online resource (XII, 340 p.) 225 1 $aLecture Notes in Computer Science,$x0302-9743 ;$v865 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-58483-8 327 $aFormal memetic algorithms -- A statistical mechanical formulation of the dynamics of genetic algorithms -- Evolutionary stability in simple classifier systems -- Nonbinary transforms for genetic algorithm problems -- Enhancing evolutionary computation using analogues of biological mechanisms -- Exploiting mate choice in evolutionary computation: Sexual selection as a process of search, optimization, and diversification -- An empirical comparison of selection methods in evolutionary algorithms -- An evolution strategy and genetic algorithm hybrid: An initial implementation and first results -- Genetic algorithms and directed adaptation -- Genetic algorithms and neighbourhood search -- A unified paradigm for parallel Genetic Algorithms -- Distributed coevolutionary genetic algorithms for multi-criteria and multi-constraint optimisation -- Inductive operators and rule repair in a hybrid genetic learning system: Some initial results -- Adaptive learning of a robot arm -- Co-evolving Co-operative populations of rules in learning control systems -- Learning anticipatory behaviour using a delayed action classifier system -- Applying a restricted mating policy to determine state space niches using immediate and delayed reinforcement -- A comparison between two architectures for searching and learning in maze problems -- Fast practical evolutionary timetabling -- Optimising a presentation timetable using evolutionary algorithms -- Genetic algorithms and flowshop scheduling: towards the development of a real-time process control system -- Genetic algorithms for digital signal processing -- Complexity reduction using expansive coding -- The application of genetic programming to the investigation of short, noisy, chaotic data series. 330 $aThis volume is based on the Workshop on Evolutionary Computing held in Leeds, U.K. in April 1994 under the sponsorship of the Society for the Study of Artificial Intelligence and Simulation of Behaviour. In addition to the 22 best papers presented at the workshop, there are two invited contributions by Ray Paton and Colin Reever. The volume addresses several aspects of evolutionary computing, particularly genetic algorithms, and its applications, for example in search, robotics, signal processing, machine learning, and scheduling. The papers are organized in sections on theoretical and biological foundations, techniques, classifier systems, and applications. 410 0$aLecture Notes in Computer Science,$x0302-9743 ;$v865 606 $aArtificial intelligence 606 $aComputers 606 $aAlgorithms 606 $aPattern recognition 606 $aBioinformatics  606 $aComputational biology  606 $aBiomathematics 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aComputation by Abstract Devices$3https://scigraph.springernature.com/ontologies/product-market-codes/I16013 606 $aAlgorithm Analysis and Problem Complexity$3https://scigraph.springernature.com/ontologies/product-market-codes/I16021 606 $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X 606 $aComputer Appl. in Life Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/L17004 606 $aMathematical and Computational Biology$3https://scigraph.springernature.com/ontologies/product-market-codes/M31000 615 0$aArtificial intelligence. 615 0$aComputers. 615 0$aAlgorithms. 615 0$aPattern recognition. 615 0$aBioinformatics . 615 0$aComputational biology . 615 0$aBiomathematics. 615 14$aArtificial Intelligence. 615 24$aComputation by Abstract Devices. 615 24$aAlgorithm Analysis and Problem Complexity. 615 24$aPattern Recognition. 615 24$aComputer Appl. in Life Sciences. 615 24$aMathematical and Computational Biology. 676 $a006.3 702 $aFogarty$b Terence C$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 12$aAISB Workshop 906 $aBOOK 912 $a996466145803316 996 $aEvolutionary computing$91487543 997 $aUNISA