Abstract
Many human and machine reasoning tasks require complicated inferences between objects and events, in which the constituting inference processes depend in turn on successive inferences on more basic binary relations. Given a set of n binary relations between m different objects or events, it is possible to infer other consistent binary relations, to check for relation inconsistency, to resolve conflicts in multiple inferences, by an efficient form of parallel computation: a binary relation inference network. The paper proposes a synchronous MIMD computational mechanism for such an inference network, and discusses its topology and physical implementation structures. Network properties and behaviors have also been studied, and some interesting results on computational passes and structural graph are obtained. >
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