Stigmergic optimization
Biologists studied the behavior of social insects for a long time. After millions of years of evolution all these species have developed incredible solutions for a wide range of problems. The intelligent solutions to problems naturally emerge from the self-organization and indirect communication of...
Gardado en:
| Autor Principal: | |
|---|---|
| Outros autores: | , |
| Formato: | Livre numérique |
| Idioma: | Anglais |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Edición: | 1st ed. 2006. |
| Series: | Studies in Computational Intelligence
31 |
| Acceso en liña: | 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: | • Stigmergic optimization, with 104 figures and 27 tables, [edited by] Ajith Abraham, Crina Grosan, Vitorino Ramos, Berlin, Springer-Verlag, 2006, 1 vol. (XVII-299 p.), Studies in computational intelligence, 3-540-34689-9 • Stigmergic Optimization, Texte imprimé, 9783540825005 • Stigmergic Optimization, Texte imprimé, 9783642071065 • Stigmergic optimization, with 104 figures and 27 tables, [edited by] Ajith Abraham, Crina Grosan, Vitorino Ramos, Berlin, Springer-Verlag, 2006, 1 vol. (XVII-299 p.), Studies in computational intelligence, 3-540-34689-9 |
Table des matières:
- Stigmergic Optimization: Inspiration, Technologies and Perspectives Stigmergic Autonomous Navigation in Collective Robotics A General Approach to Swarm Coordination using Circle Formation Stigmergic Navigation for Multi-Agent Teams in Complex Environments Physically Realistic Self-assembly Simulation System Gliders and Riders: A Particle Swarm Selects for Coherent Space-Time Structures in Evolving Cellular Automata Termite: A swarm intelligent routing algorithm for mobilewireless Ad-Hoc networks Stochastic Diffusion Search: Partial Function Evaluation In Swarm Intelligence Dynamic Optimisation Linear Multi-Objective Particle Swarm Optimization Cooperative Particle Swarm Optimizers: A Powerful and Promising Approach Parallel Particle Swarm Optimization Algorithms with Adaptive Simulated Annealing Swarm Intelligence: Theoretical Proof That Empirical Techniques are Optimal