Hybrid Neural Systems (Record no. 188803)
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fixed length control field | 05097nam a22006015i 4500 |
001 - CONTROL NUMBER | |
control field | 978-3-540-46417-4 |
003 - CONTROL NUMBER IDENTIFIER | |
control field | DE-He213 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20240423132530.0 |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
fixed length control field | cr nn 008mamaa |
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fixed length control field | 121227s2000 gw | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9783540464174 |
-- | 978-3-540-46417-4 |
024 7# - OTHER STANDARD IDENTIFIER | |
Standard number or code | 10.1007/10719871 |
Source of number or code | doi |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
Classification number | RC321-580 |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | PSAN |
Source | bicssc |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | SCI089000 |
Source | bisacsh |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | PSAN |
Source | thema |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
Classification number | 612.8 |
Edition number | 23 |
245 10 - TITLE STATEMENT | |
Title | Hybrid Neural Systems |
Medium | [electronic resource] / |
Statement of responsibility, etc | edited by Stefan Wermter, Ron Sun. |
250 ## - EDITION STATEMENT | |
Edition statement | 1st ed. 2000. |
264 #1 - | |
-- | Berlin, Heidelberg : |
-- | Springer Berlin Heidelberg : |
-- | Imprint: Springer, |
-- | 2000. |
300 ## - PHYSICAL DESCRIPTION | |
Extent | IX, 408 p. |
Other physical details | online resource. |
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-- | text |
-- | txt |
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-- | computer |
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-- | online resource |
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-- | text file |
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490 1# - SERIES STATEMENT | |
Series statement | Lecture Notes in Artificial Intelligence, |
International Standard Serial Number | 2945-9141 ; |
Volume number/sequential designation | 1778 |
505 0# - FORMATTED CONTENTS NOTE | |
Formatted contents note | An Overview of Hybrid Neural Systems -- An Overview of Hybrid Neural Systems -- Structured Connectionism and Rule Representation -- Layered Hybrid Connectionist Models for Cognitive Science -- Types and Quantifiers in SHRUTI – A Connectionist Model of Rapid Reasoning and Relational Processing -- A Recursive Neural Network for Reflexive Reasoning -- A Novel Modular Neural Architecture for Rule-Based and Similarity-Based Reasoning -- Addressing Knowledge-Representation Issues in Connectionist Symbolic Rule Encoding for General Inference -- Towards a Hybrid Model of First-Order Theory Refinement -- Distributed Neural Architectures and Language Processing -- Dynamical Recurrent Networks for Sequential Data Processing -- Fuzzy Knowledge and Recurrent Neural Networks: A Dynamical Systems Perspective -- Combining Maps and Distributed Representations for Shift-Reduce Parsing -- Towards Hybrid Neural Learning Internet Agents -- A Connectionist Simulation of the Empirical Acquisition of Grammatical Relations -- Large Patterns Make Great Symbols: An Example of Learning from Example -- Context Vectors: A Step Toward a “Grand Unified Representation” -- Integration of Graphical Rules with Adaptive Learning of Structured Information -- Transformation and Explanation -- Lessons from Past, Current Issues, and Future Research Directions in Extracting the Knowledge Embedded in Artificial Neural Networks -- Symbolic Rule Extraction from the DIMLP Neural Network -- Understanding State Space Organization in Recurrent Neural Networks with Iterative Function Systems Dynamics -- Direct Explanations and Knowledge Extraction from a Multilayer Perceptron Network that Performs Low Back Pain Classification -- High Order Eigentensors as Symbolic Rules in Competitive Learning -- Holistic Symbol Processing and theSequential RAAM: An Evaluation -- Robotics, Vision and Cognitive Approaches -- Life, Mind, and Robots -- Supplementing Neural Reinforcement Learning with Symbolic Methods -- Self-Organizing Maps in Symbol Processing -- Evolution of Symbolisation: Signposts to a Bridge between Connectionist and Symbolic Systems -- A Cellular Neural Associative Array for Symbolic Vision -- Application of Neurosymbolic Integration for Environment Modelling in Mobile Robots. |
520 ## - SUMMARY, ETC. | |
Summary, etc | Hybrid neural systems are computational systems which are based mainly on artificial neural networks and allow for symbolic interpretation or interaction with symbolic components. This book is derived from a workshop held during the NIPS'98 in Denver, Colorado, USA, and competently reflects the state of the art of research and development in hybrid neural systems. The 26 revised full papers presented together with an introductory overview by the volume editors have been through a twofold process of careful reviewing and revision. The papers are organized in the following topical sections: structured connectionism and rule representation; distributed neural architectures and language processing; transformation and explanation; robotics, vision, and cognitive approaches. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Neurosciences. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Artificial intelligence. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Computer science. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Microprocessors. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Computer architecture. |
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Neuroscience. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Artificial Intelligence. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Theory of Computation. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Processor Architectures. |
700 1# - ADDED ENTRY--PERSONAL NAME | |
Personal name | Wermter, Stefan. |
Relator term | editor. |
Relator code | edt |
-- | http://id.loc.gov/vocabulary/relators/edt |
700 1# - ADDED ENTRY--PERSONAL NAME | |
Personal name | Sun, Ron. |
Relator term | editor. |
Relator code | edt |
-- | http://id.loc.gov/vocabulary/relators/edt |
710 2# - ADDED ENTRY--CORPORATE NAME | |
Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
773 0# - HOST ITEM ENTRY | |
Title | Springer Nature eBook |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
Display text | Printed edition: |
International Standard Book Number | 9783540673057 |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
Display text | Printed edition: |
International Standard Book Number | 9783662180006 |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
Uniform title | Lecture Notes in Artificial Intelligence, |
-- | 2945-9141 ; |
Volume number/sequential designation | 1778 |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | <a href="https://doi.org/10.1007/10719871">https://doi.org/10.1007/10719871</a> |
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942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | eBooks-CSE-Springer |
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