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Titlebook: Computational Architectures Integrating Neural and Symbolic Processes; A Perspective on the Ron Sun,Lawrence A. Bookman Book 1995 Springer

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书目名称Computational Architectures Integrating Neural and Symbolic Processes
副标题A Perspective on the
编辑Ron Sun,Lawrence A. Bookman
视频video
丛书名称The Springer International Series in Engineering and Computer Science
图书封面Titlebook: Computational Architectures Integrating Neural and Symbolic Processes; A Perspective on the Ron Sun,Lawrence A. Bookman Book 1995 Springer
描述.Computational Architectures Integrating Neural and SymbolicProcesses:. .A Perspective on the State of the Art. focuses on acurrently emerging body of research. With the reemergence of neuralnetworks in the 1980s with their emphasis on overcoming some of thelimitations of symbolic AI, there is clearly a need to support someform of high-level symbolic processing in connectionist networks. Asargued by many researchers, on both the symbolic AI and connectionistsides, many cognitive tasks, e.g. language understanding and commonsense reasoning, seem to require high-level symbolic capabilities. Howthese capabilities are realized in connectionist networks is adifficult question and it constitutes the focus of this book. ..Computational Architectures Integrating Neural and SymbolicProcesses. addresses the underlying architectural aspects of theintegration of neural and symbolic processes. In order to provide abasis for a deeper understanding of existing divergent approaches andprovide insight for further developments in this field, this bookpresents: (1) an examination of specific architectures (groupedtogether according to their approaches), their strengths andweaknesses, why they work, a
出版日期Book 1995
关键词Processing; artificial intelligence; cognitive psychology; cognitive science; computer; computer science;
版次1
doihttps://doi.org/10.1007/b102608
isbn_softcover978-1-4757-8319-3
isbn_ebook978-0-585-29599-2Series ISSN 0893-3405
issn_series 0893-3405
copyrightSpringer Science+Business Media New York 1995
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Subsymbolic Parsing of Embedded Structures systems have been quite successful, for example, in modeling in-depth natural language processing [., ., .], episodic memory [., ., and problem solving [., ., .]. In such systems, knowledge is encoded in terms of explicit symbolic structures, and processing is based on handcrafted rules that operat
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An Internal Report for Connectionists has been concerned with the idea of distributed representations. Dissatisfied with the Symbolic tradition, and in search of the new, many cognitive theorists began to infiltrate connectionism in search of a new theory of mind. Like the Classicists, these theorists required that a constructed, analy
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A Two-Level Hybrid Architecture for Structuring Knowledge for Commonsense Reasoningms of representation, and it consists of two levels: one is an inference network with nodes representing concepts and links representing rules connecting concepts, and the other is a microfeature-based replica of the first level. Based on the interaction between the concept nodes and microfeature no
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A Framework for Integrating Relational and Associational Knowledge for Comprehensione ability to read it “deeply” (a fine-grain view of comprehension). A computational analogue that mimics skimming should include a representation of a set of semantic relationships about the text that can be used to summarize it and extract what is important. A computational analogue that supports a
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Examining a Hybrid Connectionist/Symbolic System for the Analysis of Ballistic SignalsI and connectionism. Some researchers .. have argued that symbolism and connectionism represent differing computational paradigms, while others have discussed merging the differing strengths and weaknesses of these approaches, as evidenced by the papers in this volume. The general consensus to date
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Symbolic Artificial Intelligence and Numeric Artificial Neural Networks: Towards a Resolution of the writings of India and Greece, this has been a central problem in philosophy. The advent of the digital computer in the 1950’s made this a central concern of computer scientists as well (.). The parallel development of the theory of computation (by John von Neumann, Alan Turing, EmilPost, Alonzo Chu
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