Reasoning about knowledge

By Ronald Fagin. 1995

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Citations in the corpus

Logic meets Probability: Towards Explainable AI Systems for Uncertain Worlds (2017, background): “Of course, having uncertainty about the actual probabilities of events raises the following question: what does the system know about its own state? If it cannot ascribe a unique probability to a proposition q, does it know of its ignorance? To be able to talk about such meta-beliefs, we turn to for”
Explanation in Artificial Intelligence: Insights from the Social Sciences (2017, methodology): “by tailoring the explanation to the human observer. Halpern and Pearl [59] already considers a simplied idea of this in their model of explanation, but other work on epistemic reasoning and planning [42, 135] and planning for interactive dialogue [143] can play a part here. These techniques will be ”
A First-Order Logic of Probability and Only Knowing in Unbounded Domains (2016, background): “For introspection, we prove general versions involving B ( α : r ) for arbitrary numbers r , and so the usual K - properties (Fagin et al. 1995) come out as special cases.”
A Social Semantics for Agent Communication Languages (2000, background): “, those with unreliable asynchronous communication Fagin et al. [1995].”
Agent-Oriented Software Engineering: The State of the Art (2009, background): “Fagin and colleagues have proposed knowledge-based programs a a paradigm for executing logical formulae which contain epistemic modalities [20, 21].”
Temporal Logics for Hyperproperties (2013, background): “This logic is defined on interpreted systems (see [26]).”
Dynamic Epistemic Logic (2007, methodology): “This would be more in line with the frameworks of [13,25], to which our analysis might be generalized.”
Engineering Societies in the Agents World II (2001, background): “Finin [10] and has been specified by the FIPA [6].”
Large Language Model Guided Tree-of-Thought (2023, background): “Developing intelligent systems that can reason has long been one of the primary goals of artiﬁcial intelligence [10, 11, 12].”
Maximize Presupposition and Gricean reasoning (2012, methodology): “With this terminology, we can give a simple semantic characterization of common belief: (11) F is common belief at w just in case F holds in every world reachable from w. 16 See also Fagin et al. 1995 and Osborne and Rubinstein 1994 for a technical discussion of common belief / common knowledge.”
Handbook of Satisfiability (2021, background): “In particular, the consistency problem for E, EM, EN, EMN is NP-complete, while for EC, ECN, EMC it is PSPACE-complete (see [74, 23]).”
Priority Structures in Deontic Logic (2014, background): “[14, 45] on temporal ‘protocols’, and [23] on deontic STIT logic.”