List of Contributors 
Foreword 
Preface 
1 Introduction: Problems for High-Level Connectionism
John A. Barnden & Jordan B. Pollack 
2 Connectionism and Compositional Semantics
David S. Touretzky 
3 Symbolic NeuroEngineering for Natural Language
Processing: A Multilevel Research Approach
Michael G. Dyer 
4 Schema Recognition for Text Understanding: An Analog
Semantic Feature Approach
Lawrence A. Bookman & Richard Alterman 
5 A Context-Free Connectionist Parser Which is not
Connectionist, But Then it is Not Really Context-Free
Either
Eugene Charniak & Eugene Santos, Jr.
6 Symbolic/Subsymbolic Sentence Analysis: Exploiting the
Best of Two Worlds
Wendy G. Lehnert
7 Developing Hybrid Symbolic/Connectionist Models
James Hendler

CONTENTS
8 Encoding Complex Symbolic Data Structures with Some
Unusual Connectionist Techniques
John A. Barnden 
9 Finding a Maximally Plausible Model of an Inconsistent
Theory
Mark Derthick 
10 The Relevance of Connectionism to AI: A Representation
and Reasoning Perspective
Lokendra Shastri 
11 Steps toward Knowledge-Intensive Connectionist Leaming
Joachim Diederich 
12 Learning Simple Arithmetic Procedures
Garrison W. Cottrell & Fu-Sheng Tsung
13 The Similarity between Connectionist and Other Parallel
Computation Models
Jiawei Hong & Xiaonan Tan 
14 Complex Features in Planning and Understanding:
Problems and Opportunities for Connectionism
Lawrence Birnbaum 
15 Conclusion
Jordan Pollack & John Barnden 
Author Index 
Subject Index