A BINARY RELATION INFERENCE NETWORK .1. GENERAL CONCEPTS

Many human and machine reasoning tasks require complicated inferences between objects and events, in which the constituting inference proces ses depends in turn on successive inferences on more basic binary rela tions. Given a set of n binary relations between in 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 rel ation inference network. This paper proposes a synchronous computation al mechanism for such an inference network, and discusses its topology and physical implementation structures. Network properties and behavi ours have also been studied, and some interesting results on computati onal passes, structural graph, unconstrained and constrained networks, energy functions and convergence conditions are obtained. Potential a pplications of the inference network for a time-referencing problem an d for an autonomous air-traffic controller are technically feasible.