000 04432nam a22005655i 4500
001 978-3-540-48999-3
003 DE-He213
005 20160624102038.0
007 cr nn 008mamaa
008 121227s1994 gw | s |||| 0|eng d
020 _a9783540489993
_9978-3-540-48999-3
024 7 _a10.1007/3-540-58483-8
_2doi
050 4 _aQA75.5-76.95
072 7 _aUYZG
_2bicssc
072 7 _aCOM037000
_2bisacsh
082 0 4 _a004.0151
_223
245 1 0 _aEvolutionary Computing
_h[electronic resource] :
_bAISB Workshop Leeds, U.K., April 11–13, 1994 Selected Papers /
_cedited by Terence C. Fogarty.
260 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c1994.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c1994.
300 _aXII, 340 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v865
505 0 _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.
520 _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.
650 0 _aComputer science.
650 0 _aComputer software.
650 0 _aArtificial intelligence.
650 0 _aOptical pattern recognition.
650 0 _aBiology
_xData processing.
650 0 _aBiology
_xMathematics.
650 1 4 _aComputer Science.
650 2 4 _aComputation by Abstract Devices.
650 2 4 _aAlgorithm Analysis and Problem Complexity.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aPattern Recognition.
650 2 4 _aComputer Appl. in Life Sciences.
650 2 4 _aMathematical Biology in General.
700 1 _aFogarty, Terence C.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783540584834
786 _dSpringer
830 0 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v865
856 4 0 _uhttp://dx.doi.org/10.1007/3-540-58483-8
942 _2EBK6630
_cEBK
999 _c35924
_d35924