| 書目名稱 | Neural-Symbolic Learning Systems | | 副標(biāo)題 | Foundations and Appl | | 編輯 | Artur S. d’Avila Garcez,Krysia B. Broda,Dov M. Gab | | 視頻video | http://file.papertrans.cn/664/663766/663766.mp4 | | 概述 | Provides the first single-source introduction to the field of knowledge-based neuro-computing.Includes real-world applications of neural-symbolic integration systems.Includes supplementary material: | | 叢書名稱 | Perspectives in Neural Computing | | 圖書封面 |  | | 描述 | Artificial Intelligence is concerned with producing devices that help or replace human beings in their daily activities. Neural-symbolic learning systems play a central role in this task by combining, and trying to benefit from, the advantages of both the neural and symbolic paradigms of artificial intelligence. .This book provides a comprehensive introduction to the field of neural-symbolic learning systems, and an invaluable overview of the latest research issues in this area. It is divided into three sections, covering the main topics of neural-symbolic integration - theoretical advances in knowledge representation and learning, knowledge extraction from trained neural networks, and inconsistency handling in neural-symbolic systems. Each section provides a balance of theory and practice, giving the results of applications using real-world problems in areas such as DNA sequence analysis, power systems fault diagnosis, and software requirements specifications. .Neural-Symbolic Learning Systems. will be invaluable reading for researchers and graduate students in Engineering, Computing Science, Artificial Intelligence, Machine Learning and Neurocomputing. It will also be of interest | | 出版日期 | Book 2002 | | 關(guān)鍵詞 | Artificial neural networks; Hybrid systems; Machine learning; Neural-symbolic integration; artificial in | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4471-0211-3 | | isbn_softcover | 978-1-85233-512-0 | | isbn_ebook | 978-1-4471-0211-3Series ISSN 1431-6854 | | issn_series | 1431-6854 | | copyright | Springer-Verlag London 2002 |
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