Foundations of a functional approach to knowledge representation.
Artificial Intelligence
Semantical considerations on nonmonotonic logic
Artificial Intelligence
On the relation between default and autoepistemic logic
Artificial Intelligence
All I know: a study in autoepistemic logic
Artificial Intelligence
Knowledge and common knowledge in a distributed environment
Journal of the ACM (JACM)
Relating autoepistemic and default logics
Proceedings of the first international conference on Principles of knowledge representation and reasoning
Quantification in autoepistemic logic
Fundamenta Informaticae - Special issue: logics for artificial intelligence
A Tractable Knowledge Representation Service with Full Introspection
Proceedings of the 2nd Conference on Theoretical Aspects of Reasoning about Knowledge
A formal treatment of incomplete knowledge bases
A formal treatment of incomplete knowledge bases
Decidable, logic-based knowledge representation
Decidable, logic-based knowledge representation
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Agents with perfect introspection may have incomplete beliefs about the world, but they possess complete knowledge about their own beliefs. This fact suggests that the beliefs of introspective agents should be completely determined by their objective beliefs, that is, those beliefs that are only about the domain in question and not about other beliefs. Introspection and logical reasoning alone should suffice to reconstruct all other beliefs from the objective ones. While this property has been shown to hold for propositional belief logics, there have so far only been negative results in the case of first-order belief logics with quantifying-in. In this paper we present a logic of belief with quantifying-in, where the beliefs of a perfectly introspective agent are indeed uniquely determined by the objective beliefs. The result is obtained by weakening the notion of belief of an existing logic that does not have this property.