Foundations of a functional approach to knowledge representation.
Artificial Intelligence
Belief, awareness, and limited reasoning
Artificial Intelligence
A guide to completeness and complexity for modal logics of knowledge and belief
Artificial Intelligence
Approximate reasoning and non-omniscient agents
TARK '92 Proceedings of the fourth conference on Theoretical aspects of reasoning about knowledge
Limited reasoning in first-order knowledge bases with full introspection
Artificial Intelligence
A Deduction Model of Belief
A nonstandard approach to the logical omniscience problem
TARK '90 Proceedings of the 3rd conference on Theoretical aspects of reasoning about knowledge
On epistemic logic and logical omniscience
TARK '86 Proceedings of the 1986 conference on Theoretical aspects of reasoning about knowledge
A decidable first-order logic for knowledge representation
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
Efficient reasoning in proper knowledge bases with unknown individuals
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
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There are not very many existing logics of belief which have both a perspicuous semantics and are computationally attractive. An exception is the logic SL, proposed by Liu, Lakemeyer, and Levesque, which allows for a decidable and often even tractable form of reasoning. While the language is first-order and hence quite expressive, it still has a number of shortcomings. For one, beliefs about beliefs are not addressed at all. For another, the names of individuals are rigid, that is, their identity is assumed to be known. In this paper, we show how both shortcomings can be overcome by suitably extending the language and its semantics. Among other things, we show that determining the beliefs of a certain kind of fully introspective knowledge bases is decidable and that unknown individuals in the knowledge base can be accommodated in a decidable manner as well.