SNAP: parallel processing applied to AI
DAN I. MOLDOVAN, Won-Uk Lee, C. Lin, M. Chung · Computer · 1992
It is argued that a viable solution for building future intelligent systems is to design special-purpose parallel computer architectures. The applications are restricted to those using semantic networks for knowledge representation. Reasoning on these networks is achieved with a marker-passing model of processing. The Semantic Network Array Processor (SNAP), a marker-passing parallel computer dedicated for natural-language and other knowledge-processing applications, is considered. Solutions for several nontrivial natural-language problems using the marker-passing approach are discussed.>