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01797nam a2200229 a 4500 |
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20171111225922.0 |
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930525s1994 njua b 001 0 eng |
| 020 |
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|a 0805811583
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| 020 |
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|a 0805811591 (pbk.)
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| 050 |
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|a 0805811583 (acid-free paper)
|b .N4845 1994
|a QA76.87
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| 082 |
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|2 20
|a 006.3
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| 245 |
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|a Neural networks for knowledge representation and inference /
|c edited by Daniel S. Levine, Manuel Aparicio IV.
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| 260 |
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|a Hillsdale, N.J. :
|b Lawrence Erlbaum Associates, Publishers,
|c c1994.
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| 300 |
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|a xv, 503 p. :
|b ill. ;
|c 27 cm.
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| 504 |
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|a Includes bibliographical references and indexes.
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| 505 |
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|a 1. Why are Neural Networks Relevant to Higher Cognitive Function? /Manuel Aparicio IV and Daniel S. Levine -- 2. On Using Analogy toReconcile Connections and Symbols / John A. Barnden -- 3. Semiotics,Meaning, and Discursive Neural Networks / Samuel J. Leven -- 4.Continuous Symbol Systems: The Logic of Connectionism / Bruce MacLennan-- 5. Representing Discrete Structures in a Hopfield-Style Network /Arun Jagota -- 6. Modeling and Stability Analysis of a TruthMaintenance System Neural Network / William Pratt Mounfield, Jr.,Ljubomir Grujic and Suresh Guddanti -- 7. Propositional Logic,Nonmonotonic Reasoning, and Symmetric Networks - On Bridging the GapBetween Symbolic and Connectionist Knowledge Representation / GadiPinkas -- 8. The Representation of Knowledge and Rules in HierarchicalNeural Networks / Thomas Jackson and James Austin -- 9. ConnectionistModels of Commonsense Reasoning / Ron Sun.
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| 650 |
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|a Neural networks (Computer science)
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| 650 |
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|a Knowledge representation (Information theory)
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| 700 |
1 |
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|a Levine, Daniel S.
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| 700 |
1 |
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|a Aparicio, Manuel
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| 952 |
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|a GrThPMO
|b 59afdeb66c5ad17d7e59e6fa
|c 952a
|d 9528
|e QA76.87.N4845 1994
|t 7
|x m
|z Books
|
