Foundations of a functional approach to knowledge representation.
Artificial Intelligence
Steps towards a first-order logic of explicit and implicit belief
Proceedings of the 1986 Conference on Theoretical aspects of reasoning about knowledge
All I know: a study in autoepistemic logic
Artificial Intelligence
A model of decidable introspective reasoning with quantifying-in
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
Decidable reasoning in first-order knowledge bases with perfect introspection
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
JELIA'10 Proceedings of the 12th European conference on Logics in artificial intelligence
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A Knowledge Representation service for a knowledge-based system (or agent) can be viewed as providing, at the very least, two operations that (a) give precise information about what is and is not believed (ASK) and (b) add new facts to the knowledge base when they become available (TELL). An appropriate model of belief for such operations should support the notion that only certain facts are believed, in particular those that have been added to a knowledge base via TELL. For logically omniscient and fully introspective agents, models of this kind lead to intractable ASK and TELL operations. In this paper, we show that tractability can be retained by giving up logical omniscience, but without sacrificing full introspection. This is done within the framework of a propositional logic of belief. In particular, the logic allows us to express that only a sentence (or finite set of them) is believed. We show that the validity of certain classes of sentences involving belief can be decided efficiently. These results are then applied to the specification of efficient TELL and ASK operations.