Parallel Problem Solving from Nature – PPSN XVI: 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part I: Lecture Notes in Computer Science, cartea 12269
Editat de Thomas Bäck, Mike Preuss, André Deutz, Hao Wang, Carola Doerr, Michael Emmerich, Heike Trautmannen Limba Engleză Paperback – 3 sep 2020
The 99 revised full papers were carefully reviewed and selected from 268 submissions. The topics cover classical subjects such as automated algorithm selection and configuration; Bayesian- and surrogate-assisted optimization; benchmarking and performance measures; combinatorial optimization; connection between nature-inspired optimization and artificial intelligence; genetic and evolutionary algorithms; genetic programming; landscape analysis; multiobjective optimization; real-world applications; reinforcement learning; and theoretical aspects of nature-inspired optimization.
Toate formatele și edițiile | Preț | Express |
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Paperback (2) | 611.80 lei 6-8 săpt. | |
Springer International Publishing – 3 sep 2020 | 611.80 lei 6-8 săpt. | |
Springer International Publishing – 2 sep 2020 | 667.75 lei 6-8 săpt. |
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Specificații
ISBN-13: 9783030581114
ISBN-10: 303058111X
Pagini: 735
Ilustrații: XXIX, 735 p. 261 illus., 169 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 1.06 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Theoretical Computer Science and General Issues
Locul publicării:Cham, Switzerland
ISBN-10: 303058111X
Pagini: 735
Ilustrații: XXIX, 735 p. 261 illus., 169 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 1.06 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Theoretical Computer Science and General Issues
Locul publicării:Cham, Switzerland
Cuprins
Automated Algorithm Selection and Configuration.- Bayesian- and Surrogate-Assisted Optimization.- Benchmarking and Performance Measures.- Combinatorial Optimization.- Connection Between Nature-Inspired Optimization and Artificial Intelligence.- Genetic and Evolutionary Algorithms.