Neural logic programming

Abstract

The authors propose a programming system that combines pattern matching of Prolog with a novel approach to logic and the control of resolution. A network of nodes and arcs together with a three-valued logic is used to indicate the connections between predicates and their consequents, and to express the flow from facts and propositions of a theory to its theorems. In this way, one can handle uncertainty and negation properly in this 'neural logic network.' A neural logic program consists of a specification of network fragments, labeled with predicates and arc weights, and they can be joined dynamically to form a tree of reasoning chains. The architecture of the neural logic computational model is left open and the authors do not intend the model to be interpreted literally as a physical architecture.