| 書目名稱 | Recruitment Learning |
| 編輯 | Joachim Diederich,Cengiz Günay,James M. Hogan |
| 視頻video | http://file.papertrans.cn/825/824314/824314.mp4 |
| 概述 | Provides an overview of recruitment learning approaches from a computational perspective.State-of-the-Art book.Written by leading experts in this field |
| 叢書名稱 | Studies in Computational Intelligence |
| 圖書封面 |  |
| 描述 | 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 f |
| 出版日期 | Book 2011 |
| 關(guān)鍵詞 | Computational Intelligence; Recruitment Learning |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-642-14028-0 |
| isbn_softcover | 978-3-642-26547-1 |
| isbn_ebook | 978-3-642-14028-0Series ISSN 1860-949X Series E-ISSN 1860-9503 |
| issn_series | 1860-949X |
| copyright | Springer-Verlag Berlin Heidelberg 2011 |
|Archiver|手機(jī)版|小黑屋|
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