Perspectives of Neural-Symbolic Integration

• Corporate Author: SpringerLink (Online service)
• Other Authors: Hammer, Barbara (Editor), Hitzler, Pascal (Editor)
• Format: Electronic eBook
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2007.
• Series: Studies in Computational Intelligence, 77
• Subjects: Engineering.; Artificial intelligence.; Applied mathematics.; Engineering mathematics.; Appl.Mathematics/Computational Methods of Engineering.; Artificial Intelligence (incl. Robotics).

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...

Table of Contents:

• 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.