Directed Graph Optical Processor

A directed graph processor and several optical realizations of its input symbolic feature vectors and the multi-processor operations required per node are given. This directed graph processor has advantages over tree and other hierarchical processors because of its large number of interconnections and its ability to adaptively add new nodes and restructure the graph. The use of the basic concepts of such a directed graph processor offer significant impact on: associative, symbolic, inference, feature space and correlation-based AI processors, as well as on knowledge base organization and procedural knowledge control of AI processors. Initial iconic alphanumeric data base results presented are most promising.