An Overview on Neural Architectures for Knowledge Representation and Inference
Short Description
The talk addresses the motives of using neural networks, the motives of
designing neural architectures for knowledge representation and inference,
potential application areas, and their open problems.
References
-
Artificial Intelligence and Neural Networks: Steps Toward Principled Integration. Honavar, V. and Uhr, L. (Ed.) New York: Academic Press. 1994
- Intelligent Hybrid Systems. Goonatilake, S. and Khebbal, S. (Ed.) London: Wiley. 1995.
- Computational Architectures Integrating Neural and Symbolic Processes. Sun, R. and Bookman, L. (Ed.) New York: Kluwer. 1995.
- Neural Networks for Knowledge Representation. Levine, D.S. and Apariciov, M. (Ed.) New York: Lawrence Erlbaum. 1994.
- Neuro-Vision Systems : Principles and Applications,Gupta, M. and Knopf, G. (Ed.) New York: IEEE Press. 1994.