Steps towards a first-order logic of explicit and implicit belief
Proceedings of the 1986 Conference on Theoretical aspects of reasoning about knowledge
Knowledge retrieval as specialized inference (artificial intelligence, sorted logic)
Knowledge retrieval as specialized inference (artificial intelligence, sorted logic)
A non-deterministic semantics for tractable inference
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Three-Valued Logics for Inconsistency Handling
JELIA '02 Proceedings of the European Conference on Logics in Artificial Intelligence
Recovering Consistency by Forgetting Inconsistency
JELIA '08 Proceedings of the 11th European conference on Logics in Artificial Intelligence
Efficient propositional constraint propagation
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Representing paraconsistent reasoning via quantified propositional logic
Inconsistency Tolerance
On the complexity of paraconsistent inference relations
Inconsistency Tolerance
Approximate Inference In Default Logic And Circumscription
Fundamenta Informaticae
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The problem of specifying, constructing, and understanding specialized, limited inference systems arises in many areas of AI. As a first step towards solving this problem this paper recommends the development of an inference engine that is limited by its inability to chain together two pieces of a representation in order to derive a third. A method for using model theory to specify limited inference is introduced and then used to specify an inference engine via a three valued logic. This inference engine is proved to be the strongest one that does no chaining, modulo the way that it divides the representation into pieces. Thus, the specification captures the set of all inferences that require no chaining. This paper also surveys and compares a number of systems that do no chaining as well as some that allow only selected forms of chaining.