|
![]() |
|||
|
||||
OverviewThis book presents a fascinating and self-contained account of ""recruitment learning"", a model and theory of fast learning in the neocortex. In contrast to the more common attractor network paradigm for long- and short-term memory, recruitment learning focuses on one-shot learning or ""chunking"" of arbitrary feature conjunctions that co-occur in single presentations. The book starts with a comprehensive review of the historic background of recruitment learning, putting special emphasis on the ground-breaking work of D.O. Hebb, W.A.Wickelgren, J.A.Feldman, L.G.Valiant, and L. Shastri. Afterwards a thorough mathematical analysis of the model is presented which shows that recruitment is indeed a plausible mechanism of memory formation in the neocortex. A third part extends the main concepts towards state-of-the-art spiking neuron models and dynamic synchronization as a tentative solution of the binding problem. The book further discusses the possible role of adult neurogenesis for recruitment. These recent developments put the theory of recruitment learning at the forefront of research on biologically inspired memory models and make the book an important and timely contribution to the field. Full Product DetailsAuthor: Joachim Diederich , Cengiz Gunay , James M. HoganPublisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K Edition: 2011 ed. Volume: 303 Dimensions: Width: 15.50cm , Height: 2.00cm , Length: 23.50cm Weight: 0.498kg ISBN: 9783642265471ISBN 10: 3642265472 Pages: 314 Publication Date: 01 December 2012 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand ![]() We will order this item for you from a manufactured on demand supplier. Table of ContentsPART I: Recruitment in Discrete Time Neural Networks .- Recruitment Learning – An Introduction.- One-shot learning - Specialization and Generalization.- Connectivity and Candidate Structures.- Representation and Recruitment.- Cognitive Applications .- PART II: Recruitment in Continuous Time Neural Networks.- Spiking Neural Networks and Temporal Binding .- Synchronised Recruitment in Cortical .- The Stability of Recruited Concepts.- Conclusions.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |