Perspectives of neural-symbolic integration
The human brain possesses the remarkable capability of understanding, interpreting, and producing language, structures, and logic. Unlike their biological counterparts, artificial neural networks do not form such a close liason with symbolic reasoning: logic-based inference mechanisms and statistica...
Enregistré dans:
| Hovedforfatter: | |
|---|---|
| Andre forfattere: | , |
| Format: | Livre numérique |
| Sprog: | Anglais |
| Udgivet: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Udgivelse: | 1st ed. 2007. |
| Serier: | Studies in Computational Intelligence
77 |
| Online adgang: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Kommentar: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Perspectives of Neural-Symbolic Integration, Texte imprimé, 9783540739531 • Perspectives of Neural-Symbolic Integration, Texte imprimé, 9783540841722 • Perspectives of Neural-Symbolic Integration, Texte imprimé, 9783642093227 • Perspectives of Neural-Symbolic Integration, Texte imprimé, 9783540739531 |
Indholdsfortegnelse:
- Structured Data and Neural Networks Kernels for Strings and Graphs Comparing Sequence Classification Algorithms for Protein Subcellular Localization Mining Structure-Activity Relations in Biological Neural Networks using NeuronRank Adaptive Contextual Processing of Structured Data by Recursive Neural Networks: A Survey of Computational Properties Markovian Bias of Neural-based Architectures With Feedback Connections Time Series Prediction with the Self-Organizing Map: A Review A Dual Interaction Perspective for Robot Cognition: Grasping as a Rosetta Stone Logic and Neural Networks SHRUTI: A Neurally Motivated Architecture for Rapid, Scalable Inference The Core Method: Connectionist Model Generation for First-Order Logic Programs Learning Models of Predicate Logical Theories with Neural Networks Based on Topos Theory Advances in Neural-Symbolic Learning Systems: Modal and Temporal Reasoning Connectionist Representation of Multi-Valued Logic Programs