Connectionist Models of Learning, Development and Evolution: Proceedings of the Sixth Neural Computation and Psychology Workshop, Liège, Belgium, 16-18 September 2000

by Robert M. French (Editor), Jacques P. Sougne (Editor)

Overview

Connectionist Models of Learning, Development and Evolution comprises a selection of papers presented at the Sixth Neural Computation and Ps ychology Workshop - the only international workshop devoted to connect ionist models of psychological phenomena. With a main theme of neural network modelling in the areas of evolution, learning, and development , the papers are organized into six sections: The neural basis of cogn ition Development and category learning Implicit learning Social cogni tion Evolution Semantics Covering artificial intelligence, mathematics , psychology, neurobiology, and philosophy, it will be an invaluable r eference work for researchers and students working on connectionist mo delling in computer science and psychology, or in any area related to cognitive science.

Product Details

ISBN-13:	9781447102816
Publisher:	Springer-Verlag New York, LLC
Publication date:	12/06/2012
Series:	Perspectives in Neural Computing
Sold by:	Barnes & Noble
Format:	eBook
File size:	9 MB

Table of Contents

SECTION I: Neural Basis of Cognition.- 1. Applying Neuroanatomical Distinctions to Connectionist Cognitive Modelling.- 2. Pseudopatterns and Dual-Network Memory Models: Advantages and Shortcomings.- 3. A Learning Algorithm for Synfue Chains.- 4. Towards a Spatio-Temporal Analysis Tool for fMRI Data: An Application to Depth-from-Motion Processing in Humans.- 5. A Simple Model Exhtbiting Scalar Timing.- 6. Modularity and Specialized Learning in the Organization of Behaviour.- 7. Modeling Modulatory Aspects in Association Processes.- 8. Recognition of Novelty Made Easy: Constraints of Channel Capacity on Generative Networks.- 9. A Biologically Plausible Maturation of an ART Network.- SECTION II: Development and Category Learning.- 10. Developing Knowledge about Living Things: A Connectionist Investigation.- 11. Paying Attention to Relevant Dimensions: A Localist Approach.- 12. Coordinating Multiple Sensory Modalities While Learning to Reach.- 13. Modelling Cognitive Development with Constructivist Neural Networks.- 14. Learning Action Affordances and Action Schemas.- 15. A Three-Layer Configural Cue Model ofCategory Learning Rates.- 16. A Revival of Turing’s Forgotten Connectionist Ideas: Exploring Unorganized Machines.- 17. Visual Crowding and Category-Specific Deficits: A Neural Network Model.- SECTION III: Implicit Learning.- 18.Implicit Learning of Regularities in Western Tonal Music by Self-Organization.- 19. Rules vs. Statistics in Implicit Learning of Biconditional Grammars.- 20. Hidden Markov Model Interpretations of Neural Networks.- SECTION IV: Models of Social Cognition.- 21. A Connectionist Model of Person Perception and Stereotype Formation.- 22. Learning about an Absent Cause: Discounting and Augmentation of Positively and Independently Related Causes.-SECTION V: Evolution.- 23. Exploring the Baldwin Effect in Evolving Adaptable Control Systems.- 24. Borrowing Dynamies from Evolution: Association using Catalytie Network Models.- 25. Evolving Modular Architectures for Neural Networks.- 26. Evolution, Development and Learning - A Nested Hierarchy?.- SECTION VI: Semantics.- 27. Learning Lexical Properties from Word Usage Patterns: Which Context Words Should be Used?.- 28. Associative Computation and Associative Prediction.- 29. The Development of Small-World Semantie Networks.- 30. What is the Dimensionality of Human Semantie Space?.- Author Index.