Abstract
The gap between symbol processing and non-symbol processing is investigated. Predicate logic and neural network were selected as the typical symbol and non-symbol processing respectively. An intermediate form was introduced to represent both of them in the same framework. Using this intermediate form the characteristics of these two methods of representation and processing are analyzed and compared. Then the syntax of predicate logic is expanded in order to reduce this gap. A way of applying this extended logic to database in order to represent it in a few predicate formulae is discussed.
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References
S. Ohsuga; Symbol Processing by Non-Symbol Processor, Proc. PRICAI’96
S. Ohsuga; Integration of Different Information Processing Methods, (to appear in) Deep Fusion of Computational and Symbolic Processing, (eds. F. Furuhashi, S. Tano, and H.A. Jacobsen), Springer, 2000
Hiroshi Tsukimoto: Symbol pattern integration using multi-linear functions, (to appear in) Deep Fusion of Computational and Symbolic Processing, T. Furuhashi, S. Tano, and H.A. Jacobsen), Springer, 2000
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© 2000 Springer-Verlag Berlin Heidelberg
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Ohsuga, S. (2000). The Gap between Symbol and Non-symbol Processing. In: Mizoguchi, R., Slaney, J. (eds) PRICAI 2000 Topics in Artificial Intelligence. PRICAI 2000. Lecture Notes in Computer Science(), vol 1886. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44533-1_6
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DOI: https://doi.org/10.1007/3-540-44533-1_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67925-7
Online ISBN: 978-3-540-44533-3
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