A Theory of Diagnosis from First Principles

By Raymond Reiter. 1986

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Citations in the corpus

Explanation in Artificial Intelligence: Insights from the Social Sciences (2017, background): “[155, 97]) and the concept of explanatory power of a set of hypotheses is defined as the set of manifestations those hypotheses account for [1].”
Decomposable negation normal form (2001, methodology): “A diagnosis of a system description ( 1; A ; O ) and observation ﬁ is an A -instantiation consistent with 1 [ f ﬁ g [Reiter 1987; de Kleer et al. 1992].”
A Survey on Software Fault Localization (2016, methodology): “While using model-based diagnosis [301], it is assumed that a correct model of each program being diagnosed is available.”
Non-Standard Reasoning Services for the Debugging of Description Logic Terminologies (2003, unknown): “, introducing TMS [Doyle, 1979] or Diagnosis [Reiter, 1987]) and The orem Proving (recently [Fiedler, 2001]).”
Finding All Justifications of OWL DL Entailments (2007, methodology): “A plausible one is to employ a variation of the classical Hitting Set Tree (HST) algorithm [7].”
Robot task planning and explanation in open and uncertain worlds (2015, background): “In terms of explaining why a goal cannot be reached, there is some overlap with counterfactual reasoning [27], belief revision [9] and consistency-based diagnosis [39].”
Reconciling theory with observations: elements of a diagnostic approach to model evaluation (2008, background): “…conflicts with the way the system is observed (or supposed) to behave, the diagnostic problem is to determine those components of the model, which when assumed to be functioning properly, will explain the discrepancy between the computed and observed system behaviour (adapted from Reiter, 1987).”
Robot task planning and explanation in open and uncertain worlds (2017, background): “In terms of explaining why a goal cannot be reached, there is some overlap with counterfactual reasoning [27], belief revision [9] and consistency-based diagnosis [39].”
Towards Trustable Explainable AI (2020, background): “These recent re-sults build on work from the 80s and 90s, ﬁrst on model-based diagnosis [ Reiter, 1987 ] , and then on computing primes of (Boolean) functions [ Rymon, 1994 ] , but also suggest that additional connections between analysis of ML models and other areas of AI can be established.”
On Relating Explanations and Adversarial Examples (2019, background): “This property is tightly related with the concept of hitting set duality between diagnoses and conflicts in model-based diagnosis [45], but also with computation of prime implicants and implicates of Boolean functions [51].”
A review of process fault detection and diagnosis: Part II: Qualitative models and search strategies (2003, background): “Reiter (1987) has shown how default logic can be used for reasoning about multiple faults or causes for an abnormality.”