A Hypergraph Representation for Deductive Reasoning Systems

Eleventh Midwest Artificial intelligence and Cognitive Science Conference

Volume

Eleventh Midwest Artificial intelligence and Cognitive Science Conference

Contents

Hypergraphs are often used to represent knowledge bases because of their accurate depiction of causal links between facts. Deduction can be computed over such a knowledge base by complete hypergraph traversal. Efficient structuring of such hypergraphs can reduce time in deductive computation as well as space in vertex and hyperedge storage. In this work, we transform a hypergraph storing a knowledge base into a more efficient representation. By representing only part of the ground instantiation of the internal knowledge base, we attain a great space reduction. This partial representation is accomplished by storing non-ground, intensional predicates and by performing individual instantiations on these. In this paper, we present the implementation of these techniques and compare them to those used in computer system INDED (pronounced "indeed").