** CONNECTIONIST-SYMBOLIC INTEGRATION **

 
This book is concerned with the development, analysis, and application
of hybrid connectionist-symbolic models in artificial intelligence
and cognitive science, drawing contributions from an international
group of leading experts. It describes and compares a variety of models
in this area. Thus, it serves as a well-balanced report on the state of
the art in this area.

This book is the outgrowth of The IJCAI Workshop on Connectionist-Symbolic
Integration: From Unified to Hybrid Approaches}, which was held for two days
during August 19-20 in Montreal, Canada, in conjunction with the Fourteenth
International Joint Conference on Artificial Intelligence (IJCAI'95).
 
 

1. An Introduction to Connectionist Symbolic Integration
R. Sun

part 1: Reviews and Overviews

2. An overview of strategies for neurosymbolic integration
M. Hilario

3. Task structure and computational level: architectural issues in
symbolic-connectionist integration
R. Khosla and T. Dillon

4. Cognitive aspects of neurosymbolic integration
Y. Lallement and F. Alexandre
 

5. A first approach to a taxonomy of fuzzy-neural systems
L. Magdalena

part 2:
Learning in Multi-Module Systems

6. A hybrid learning model of abductive reasoning
T. Johnson and J. Zhang

7. A hybrid learning model of reactive sequential decision making
R. Sun and T. Peterson

8. A preprocessing model for integrating CBR and prototype-based
neural network
M. Malek and B. Amy

9. A neurosymbolic system with 3 levels
B. Orsier and A. Labbi

10. A distributed platform for symbolic-connectionist integration
J. C. Gonzalez, J. R. Velasco, C. A. Iglesias
 

part 3:
Representing Symbolic Knowledge

11. Micro-level hybridization in DUAL
B. Kokinov

12. An integrated symbolic/connectionist model of parsing
S. Stevenson

13. A hybrid system framework for disambiguating word senses
X. Wu, M. McTear, P. Ojha, H. Dai

14. A localist network architecture for logical inference
N. Park and D. Robertson

15. Distributed associative memory
J. Austin

16. Symbolic neural networks derived from stochastic grammar domain models
E. Mjolsness
 

Part 4:
Learning Distributed Representation

17. Holographic reduced representation
T. Plate

18. Distributed representations for terms in hybrid reasoning systems
A. Sperduti, A. Starita, C. Goller

19. Learning distributed representation
R. Krosley and M. Misra

Conclusion
20. Conclusion
F Alexandre

For a closed related book, entitled
"Computational Architectures Integrating Symbolic and Connectionist Processing"
(edited by Ron Sun and Larry Bookman, published by Kluwer Academic Publishers)
see my Web page for information
 
 
 

Go to Prof. Ron Sun's Homepage