Optical Symbolic Computing

John A. Neff

doi:10.1117/12.948551

16 December 1989 Optical Symbolic Computing

John A. Neff

Proceedings Volume 0977, Real-Time Signal Processing XI; (1989) https://doi.org/10.1117/12.948551
Event: 32nd Annual International Technical Symposium on Optical and Optoelectronic Applied Science and Engineering, 1988, San Diego, CA, United States

Abstract

Experiments originating from Gestalt psychology have shown that representing information in a symbolic form provides a more effective means to understanding. Computer scientists have been struggling for the last two decades to determine how best to create, manipulate, and store collections of symbolic structures. In the past, much of this struggling led to software innovations because that was the path of least resistance. For example, the development of heuristics for organizing the searching through knowledge bases was much less expensive than building massively parallel machines that could search in parallel. That is now beginning to change with the emergence of parallel architectures which are showing the potential for handling symbolic structures. This paper will review the relationships between symbolic computing and parallel computing architectures, and will identify opportunities for optics to significantly impact the performance of such computing machines. Although neural networks are an exciting subset of massively parallel computing structures, this paper will not touch on this area since it is receiving a great deal of attention in the literature. That is, the concepts presented herein do not consider the distributed representation of knowledge.

Citation Download Citation

John A. Neff "Optical Symbolic Computing", Proc. SPIE 0977, Real-Time Signal Processing XI, (16 December 1989); https://doi.org/10.1117/12.948551

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