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Hybrid Neural Systems

  • Conference proceedings
  • © 2000

Overview

Editors:
  1. Stefan Wermter

    1. University of Sunderland, Sunderland, United Kingdom

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  2. Ron Sun

    1. CECS Department, University of Missouri-Colombia , Columbia, USA

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 1778)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

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Table of contents (27 papers)

  1. Front Matter

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  2. An Overview of Hybrid Neural Systems

    1. An Overview of Hybrid Neural Systems

      • Stefan Wermter, Ron Sun
      Pages 1-13

  3. Structured Connectionism and Rule Representation

    1. Layered Hybrid Connectionist Models for Cognitive Science

      • Jerome Feldman, David Bailey
      Pages 14-27

    2. Types and Quantifiers in SHRUTI – A Connectionist Model of Rapid Reasoning and Relational Processing

      • Lokendra Shastri
      Pages 28-45

    3. A Recursive Neural Network for Reflexive Reasoning

      • Steffen Hölldobler, Yvonne Kalinke, Jörg Wunderlich
      Pages 46-62

    4. A Novel Modular Neural Architecture for Rule-Based and Similarity-Based Reasoning

      • Rafal Bogacz, Christophe Giraud-Carrier
      Pages 63-77

    5. Addressing Knowledge-Representation Issues in Connectionist Symbolic Rule Encoding for General Inference

      • Nam Seog Park
      Pages 78-91

    6. Towards a Hybrid Model of First-Order Theory Refinement

      • Nelson A. Hallack, Gerson Zaverucha, Valmir C. Barbosa
      Pages 92-106

  4. Distributed Neural Architectures and Language Processing

    1. Dynamical Recurrent Networks for Sequential Data Processing

      • Stefan C. Kremer, John F. Kolen
      Pages 107-122

    2. Fuzzy Knowledge and Recurrent Neural Networks: A Dynamical Systems Perspective

      • Christian W. Omlin, Lee Giles, K. K. Thornber
      Pages 123-143

    3. Combining Maps and Distributed Representations for Shift-Reduce Parsing

      • Marshall R. Mayberry III, Risto Miikkulainen
      Pages 144-157

    4. Towards Hybrid Neural Learning Internet Agents

      • Stefan Wermter, Garen Arevian, Christo Panchev
      Pages 158-174

    5. A Connectionist Simulation of the Empirical Acquisition of Grammatical Relations

      • William C. Morris, Garrison W. Cottrell, Jeffrey Elman
      Pages 175-193

    6. Large Patterns Make Great Symbols: An Example of Learning from Example

      • Pentti Kanerva
      Pages 194-203

    7. Context Vectors: A Step Toward a “Grand Unified Representation”

      • Stephen I. Gallant
      Pages 204-210

    8. Integration of Graphical Rules with Adaptive Learning of Structured Information

      • Paolo Frasconi, Marco Gori, Alessandro Sperduti
      Pages 211-225

  5. Transformation and Explanation

    1. Lessons from Past, Current Issues, and Future Research Directions in Extracting the Knowledge Embedded in Artificial Neural Networks

      • Alan B. Tickle, Frederic Maire, Guido Bologna, Robert Andrews, Joachim Diederich
      Pages 226-239

    2. Symbolic Rule Extraction from the DIMLP Neural Network

      • Guido Bologna
      Pages 240-254

    3. Understanding State Space Organization in Recurrent Neural Networks with Iterative Function Systems Dynamics

      • Peter Tiňo, Georg Dorffner, Christian Schittenkopf
      Pages 255-269

    4. Direct Explanations and Knowledge Extraction from a Multilayer Perceptron Network that Performs Low Back Pain Classification

      • Marilyn L. Vaughn, Steven J. Cavill, Stewart J. Taylor, Michael A. Foy, Anthony J. B. Fogg
      Pages 270-285
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Keywords

About this book

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.

Editors and Affiliations

  • University of Sunderland, Sunderland, United Kingdom

    Stefan Wermter

  • CECS Department, University of Missouri-Colombia , Columbia, USA

    Ron Sun

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