Challenges for computational intelligence
In the year 1900 at the International Congress of Mathematicians in Paris David Hilbert delivered what is now considered the most important talk ever given in the history of mathematics, proposing 23 major problems worth working at in the future. One hundred years later the impact of this talk is st...
Tallennettuna:
| Päätekijä: | |
|---|---|
| Muut tekijät: | , , |
| Aineistotyyppi: | Livre numérique |
| Kieli: | Anglais |
| Julkaistu: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Painos: | 1st ed. 2007. |
| Sarja: | Studies in Computational Intelligence
63 |
| Linkit: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Huomautus: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Challenges for Computational Intelligence, Texte imprimé, 9783540719830 • Challenges for Computational Intelligence, Texte imprimé, 9783540837480 • Challenges for Computational Intelligence, Texte imprimé, 9783642091162 • Challenges for Computational Intelligence, Texte imprimé, 9783540719830 |
Sisällysluettelo:
- What Is Computational Intelligence and Where Is It Going? New Millennium AI and the Convergence of History The Challenges of Building Computational Cognitive Architectures Programming a Parallel Computer: The Ersatz Brain Project The Human Brain as a Hierarchical Intelligent Control System Artificial Brain and OfficeMate TR based on Brain Information Processing Mechanism Natural Intelligence and Artificial Intelligence: Bridging the Gap between Neurons and Neuro-Imaging to Understand Intelligent Behaviour Computational Scene Analysis Brain-, Gene-, and Quantum Inspired Computational Intelligence: Challenges and Opportunities The Science of Pattern Recognition. Achievements and Perspectives Towards Comprehensive Foundations of Computational Intelligence Knowledge-Based Clustering in Computational Intelligence Generalization in Learning from Examples A Trend on Regularization and Model Selection in Statistical Learning: A Bayesian Ying Yang Learning Perspective Computational Intelligence in Mind Games Computer Go: A Grand Challenge to AI Noisy Chaotic Neural Networks for Combinatorial Optimization