| 書目名稱 | Learning in Natural and Connectionist Systems | | 副標(biāo)題 | Experiments and a Mo | | 編輯 | R. Hans Phaf | | 視頻video | http://file.papertrans.cn/583/582967/582967.mp4 | | 圖書封面 |  | | 描述 | Modern research in neural networks has led to powerfulartificial learning systems, while recent work in the psychology ofhuman memory has revealed much about how natural systems.really.learn, including the role of unconscious, implicit, memory processes.Regrettably, the two approaches typically ignore each other. Thisbook, combining the approaches, should contribute to their mutualbenefit. .New empirical work is presented showing dissociations between implicitand explicit memory performance. Recently proposed explanations forsuch data lead to a new connectionist learning procedure: CALM(Categorizing and Learning Module), which can learn with or withoutsupervision, and shows practical advantages over many existingprocedures. Specific experiments are simulated by a network model(ELAN) composed of CALM modules. A working memory extension to themodel is also discussed that could give it symbol manipulationabilities. .The book will be of interest to memory psychologists andconnectionists, as well as to cognitive scientists who in the pasthave tended to restrict themselves to symbolic models. . | | 出版日期 | Book 1994 | | 關(guān)鍵詞 | evaluation; learning systems; neural networks | | 版次 | 1 | | doi | https://doi.org/10.1007/978-94-011-0840-9 | | isbn_softcover | 978-94-010-4362-5 | | isbn_ebook | 978-94-011-0840-9 | | copyright | Springer Science+Business Media Dordrecht 1994 |
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