00000cmm a22000004a 4500 UP-99796217611916099 Buklod 20250624140706.0 m go j cr |n |||auu|a 250624s2011 gw ||||go||j| ||||||eng d 9783642140280 (eBook) 3642140289 (eBook) (iLib)UPD-00254206782 CSt DMLR rda eng DMLUC QP 363.3 D54 2011eb Diederich, Joachim author. Recruitment learning by Joachim Diederich, Cengiz Günay, James M. Hogan. Berlin Heidelberg Springer 2011. online resource (x, 314 pages) illustrations (some color) text rdacontent computer rdamedia online resource rdacarrier Studies in computational intelligence 1860-949X v. 303 Includes bibliographical references and indexes PART 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. IP-based subscription, access limited to within on-campus computer network. Access via Electronic Resources of the UPD University Library Website. This 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. Electronic reproduction. New York SpringerLink 2011. Available via World Wide Web through SpringerLink. Neural networks (Neurobiology) Neural computers. Connectionism. Machine learning. Günay, Cengiz author. Hogan, James (James M.) author. Available for University of the Philippines Diliman via SpringerLink. Click here to access http://link.springer.com/book/10.1007/978-3-642-14028-0 FO UPD DMLR QP 363.3 D54 2011eb Electronic Resource