Stochastic algorithms : foundations and applications : international symposium, SAGA 2001, Berlin, Germany, December 13-14, 2001 : proceedings
SAGA 2001, the ?rst Symposium on Stochastic Algorithms, Foundations and Applications, took place on December 13 14, 2001 in Berlin, Germany. The present volume comprises contributed papers and four invited talks that were included in the ?nal program of the symposium. Stochastic algorithms constitut...
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| Otros Autores: | |
| Formato: | Livre numérique |
| Lenguaje: | Anglais |
| Publicado: |
Berlin [etc.] :
Springer
[20..].
Cham : Springer Nature |
| Colección: | Lecture notes in computer science
2264 |
| Materias: | |
| Acceso en línea: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Stochastic algorithms, foundations and applications, international symposium, SAGA 2001, Berlin, Germany, December 13-14, 2001, proceedings, Kathleen Steinhöfel (Ed.), 2001, Berlin, Springer, 1 vol. (VIII-202 p.), Lecture notes in computer science, 3-540-43025-3 • Stochastic Algorithms: Foundations and Applications, Texte imprimé, 9783662212448 |
Tabla de Contenidos:
- Randomized Communication Protocols
- Optimal Mutation Rate Using Bayesian Priors for Estimation of Distribution Algorithms
- An Experimental Assessment of a Stochastic, Anytime, Decentralized, Soft Colourer for Sparse Graphs
- Randomized Branching Programs
- Yet Another Local Search Method for Constraint Solving
- An Evolutionary Algorithm for the Sequence Coordination in Furniture Production
- Evolutionary Search for Smooth Maps in Motor Control Unit Calibration
- Some Notes on Random Satisfiability
- Prospects for Simulated Annealing Algorithms in Automatic Differentiation
- Optimization and Simulation: Sequential Packing of Flexible Objects Using Evolutionary Algorithms
- Stochastic Finite Learning
- Sequential Sampling Algorithms: Unified Analysis and Lower Bounds
- Approximate Location of Relevant Variables under the Crossover Distribution.