Genetic Programming
Editat de Wolfgang Banzhaf, Riccardo Poli, Marc Schoenauer, Terence C. Fogartyen Limba Engleză Paperback – 25 mar 1998
The volume presents 12 revised full papers and 10 short presentations carefully selected for inclusion in the book. The papers are organized in topical sections on experimental and theoretical studies; algorithms, representations and operators; and applications.
Preț: 317.77 lei
Preț vechi: 397.21 lei
-20%
Puncte Express: 477
Carte tipărită la comandă
Livrare economică 27 iulie-10 august
Livrare prin curier în România Termenul estimat este afișat lângă disponibilitate.
Transport gratuit de la 400.00 lei Plată online sau ramburs, în funcție de opțiunile comenzii.
Retur gratuit în 14 zile Comandă securizată și suport în română.
Specificații
ISBN-13: 9783540643609
ISBN-10: 3540643605
Pagini: 248
Ilustrații: X, 238 p.
Dimensiuni: 155 x 235 x 14 mm
Greutate: 0.38 kg
Ediția:1998
Editura: Springer
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3540643605
Pagini: 248
Ilustrații: X, 238 p.
Dimensiuni: 155 x 235 x 14 mm
Greutate: 0.38 kg
Ediția:1998
Editura: Springer
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
A review of theoretical and experimental results on schemata in genetic programming.- Where does the good stuff go, and why? how contextual semantics influences program structure in simple genetic programming.- Fitness causes bloat: Mutation.- Concepts of inductive genetic programming.- Immediate transfer of global improvements to all individuals in a population compared to automatically defined functions for the EVEN-5,6-PARITY problems.- Non-destructive depth-dependent crossover for genetic programming.- Grammatical evolution: Evolving programs for an arbitrary language.- Genetic programming bloat with dynamic fitness.- Speech sound discrimination with genetic programming.- Efficient evolution of asymmetric recurrent neural networks using a PDGP-inspired two-dimensional representation.- A cellular-programming approach to pattern classification.- Evolving coupled map lattices for computation.- Genetic programming for automatic design of self-adaptive robots.- Genetic modelling of customer retention.- An evolutionary hybrid metaheuristic for solving the vehicle routing problem with heterogeneous fleet.- Building a genetic programming framework: The added-value of design patterns.- Evolutionary computation and the tinkerer’s evolving toolbox.- A dynamic lattice to envolve hierarchically shared subroutines.