Evolutionary Computing AISB International Workshop, Manchester, UK, April 7-8, 1997. Selected Papers.

This book constitutes the refereed post-workshop proceedings of the AISB International Workshop on Evolutionary Computing, held in Manchester, UK, in April 1997. The 22 strictly reviewed and revised full papers presented were selected for inclusion in the book after two rounds of refereeing. The pap...

Full description

Bibliographic Details
Other Authors: Corne, David (Editor), Shapiro, Jonathan L. (Editor)
Format: eBook
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 1997, 1997
Edition:1st ed. 1997
Series:Lecture Notes in Computer Science
Subjects:
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
LEADER 03523nmm a2200373 u 4500
001 EB000659598
003 EBX01000000000000000512680
005 00000000000000.0
007 cr|||||||||||||||||||||
008 140122 ||| eng
020 |a 9783540695783 
100 1 |a Corne, David  |e [editor] 
245 0 0 |a Evolutionary Computing  |h Elektronische Ressource  |b AISB International Workshop, Manchester, UK, April 7-8, 1997. Selected Papers.  |c edited by David Corne, Jonathan L. Shapiro 
250 |a 1st ed. 1997 
260 |a Berlin, Heidelberg  |b Springer Berlin Heidelberg  |c 1997, 1997 
300 |a X, 314 p  |b online resource 
505 0 |a Simulating pricing behaviours using a genetic algorithm -- Biologically inspired computational ecologies: A case study -- Modelling bounded rationality using evolutionary techniques -- The abstract theory of evolution of the living -- An evolutionary algorithm for single objective nonlinear constrained optimization problems -- On recombinative sampling -- The evolution of mutation, plasticity and culture in cyclically changing environments -- On the structure and transformation of landscapes -- Island model genetic algorithms and linearly separable problems -- Empirical validation of the performance of a class of transient detector -- The contruction and evaluation of decision trees: A comparison of evolutionary and concept learning methods -- Parallel distributed genetic programming applied to the evolution of natural language recognisers -- Scheduling planned maintenance of the South Wales region of the National Grid -- Solving generic scheduling problems with a distributed genetic algorithm -- Directing the search of evolutionary and neighbourhood-search optimisers for the flowshop sequencing problem with an idle-time heuristic -- Multiobjective genetic algorithms for pump scheduling in water supply -- Use of rules and preferences for schedule builders in genetic algorithms for production scheduling -- A Voxel based approach to evolutionary shape optimisation -- Phase transition networks: A modelling technique supporting the evolution of autonomous agents' tactical and operational activities -- An evolutionary, agent-assisted strategy for conceptual design space decomposition -- Task scheduling with use of classifier systems 
653 |a Bioinformatics 
653 |a Computer science 
653 |a Computational and Systems Biology 
653 |a Artificial Intelligence 
653 |a Algorithms 
653 |a IT in Business 
653 |a Artificial intelligence 
653 |a Theory of Computation 
653 |a Business information services 
700 1 |a Shapiro, Jonathan L.  |e [editor] 
041 0 7 |a eng  |2 ISO 639-2 
989 |b SBA  |a Springer Book Archives -2004 
490 0 |a Lecture Notes in Computer Science 
028 5 0 |a 10.1007/BFb0027161 
856 4 0 |u https://doi.org/10.1007/BFb0027161?nosfx=y  |x Verlag  |3 Volltext 
082 0 |a 006.3 
520 |a This book constitutes the refereed post-workshop proceedings of the AISB International Workshop on Evolutionary Computing, held in Manchester, UK, in April 1997. The 22 strictly reviewed and revised full papers presented were selected for inclusion in the book after two rounds of refereeing. The papers are organized in sections on evolutionary approaches to issues in biology and economics, problem structure and finite landscapes, evolutionary machine learning and classifier systems, evolutionary scheduling, and more techniques and applications of evolutionary algorithms