Hybrid optical inference machines: architectural considerations

Fast reconfigurable optical image switching/routing system

A novel system that is capable of switching/routing two-dimensional images in arbitrary configurations is described. The switching network can be reconfigured in a few microseconds with high light efficiency.

Parallel electro-optical rule-based system for fast execution of expert systems

The slow execution speed of current rule-based systems has restricted their application areas. Multiprocessor architectures have been proposed to overcome this limitation. However, as the number of processors in a multiprocessor system grows, so does the cost of communication between processors or between processor and memory units. The use of optics for a fast and parallel implementation of rule-based systems is proposed. The proposed optical system is hybrid in nature, using electronics for the user interface and optics for the rule-based inference engine. The proposed system uses twodimensional planes as basic computational entities and is therefore able to provide concurrent rule processing. Furthermore, it provides highly efficient implementation of the basic operations needed in rule-based systems; namely, matching, selection, and rule firing. The execution speed of the proposed system is theoretically estimated and is shown to be potentially of orders of magnitude faster than current electronic system.

Inference engine for expert system by using optical array logic

A method of implementing an inference engine for an expert system by using optical array logic is presented. Optical array logic is a technique for parallel neighborhood operations based on spatial coding and two-dimensional correlation. The processing capability of optical array logic is useful for the efficient execution of an inference operation in artificial intelligence problems. Inference proceeds with the help of a token propagation technique in which the knowledge is expressed as spatial patterns and processed collectively with parallel neighborhood operations in optical array logic. With several additional functions, an expert system can be constructed by using the inference technique.

Optical expert system based on matrix-algebraic formulation

This paper describes an expert system paradigm based on matrix algebra. The knowledge base of the expert system is stored in binary matrices, while the learning and inference processes are done by matrix algebra operations. This method is highly parallel and can take full advantage of the inherent parallelism and connectivity of optics. An optoelectronic architecture that implements this system is presented. In addition, the method is compared with the sequential search methods written in the programming language PROLOG to illustrate their differences and commonalities.

Optical production systems using neural networks and symbolic substitution

Two optical implementations of production systems are advanced. The production systems operate on a knowledge base where facts and rules are encoded as formulas in propositional calculus. The first implementation is a binary neural network. An analog neural network is used to include reasoning with uncertainties. The second implementation uses a new optical symbolic substitution correlator. This implementation is useful when a set of similar situations has to be handled in parallel on one processor.

Parallel optical syntactic pattern recognizers

There are many pattern recognition problems where the pattern's structural information is important. In these problems, a syntactic method of pattern recognition is of value. In this paper, both parallel syntactic pattern recognition algorithm and optical architecture implementation approaches are described. In particular, the applications of syntactic pattern recognition algorithm to shape classification are illustrated. A number of parallel optical syntactic pattern coding methods, a structural matched filter and associative memory filter, and an optical symbolic substitution syntactic parser are discussed.

Real-time optical expert systems

Optics has advantages for overcoming limitations arising when applying existing electronic technologies to real-time parallel computation. In particular, spatial light modulators (SLMs) permit simultaneous storage, multiplication, and/or complex interconnection. A simple expert uses an SLM crossbar switch to provide a flexible and fast implementation of combinatorial logic. A second expert system, illustrated using medical diagnosis, uses the Bayes theorem to update recursively the probabilities of various illnesses given additional symptom information. The a priori probability matrices are stored in SLMs which provide matrix-vector multiplication and interconnection. Computation of the best next symptom question is possible because of the high speed.

Model-based knowledge-based optical processors

An efficient 3-D object-centered knowledge base is described. The ability to on-line generate a 2-D image projection or range image for any object/viewer orientation from this knowledge base is addressed. Applications of this knowledge base in associative processors and symbolic correlators are then discussed. Initial test results are presented for a multiple degree of freedom object recognition problem. These include new techniques to achieve object orientation information and two new associative memory matrix formulations.

Optical expert systems

A general approach to using spatial light modulators in expert systems and in related AI methods is discussed. The information capacity of such system can far exceed the capacity of the spatial light modulator itself.