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Evidential Reasoning in Semantic Networks: A Formal Theory

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Proceedings of the Ninth International Joint Conference on Artificial Intelligence. Knowledge Representation. Pages 465-473.

Abstract

This paper presents an evidential approach to kn o wledge representation and inference wherein the prin ciple of maximum entropy is applied to deal with uncertainty and incompleteness. It focuses on a restricted rep resentation language - similar in expressive power to se mantic network formalisms. and develops a formal th eo ry of evidential inheritance wtthin this language. The th eo ry applies to a limited, but we think interesting, class o f inh eritance problems including those that involve exceptions and multiple inheritance hierarchies. The lan guage and the accompanying evidential inference structure provide a natural treatment of defaults and conllicting information. The evidence combination rule propos ed in this paper is incremental, commutative and C~ ssoc iative and hence, shares most of the attractive fea tures o f the Dempster-Shafer evidence combination rul e. Furthermore. it is demonstrably better than the Dempster-Shafer rule in the context of the problems a ddr ess ed in this paper. The resulting theory can be implem ented as a highly parall el (connectionist) network made up o f active elements that can solve inheritance pro bl ems in time proportional to the depth of the conceptual hierarchy.

Lokendra Shastri, and Jerome A. Feldman. 1985. Evidential Reasoning in Semantic Networks: A Formal Theory. In Proceedings of the Ninth International Joint Conference on Artificial Intelligence, IJCAI-85. IJCAI, 465–473. https://ijcai.org/proceedings/1985/92
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