activity
19972022
most citedWhy Is Diagnosis Using Belief Networks Insensitive to Imprecision In Probabilities?

62 citations · 161 across the 16 of their papers we have counts for

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13 papers · 1 filter

cs.AI2014

Query DAGs: A Practical Paradigm for Implementing Belief Network Inference

Adnan Darwiche, Gregory M. Provan

We describe a new paradigm for implementing inference in belief networks, which relies on compiling a belief network into an arithmetic expression called a Query DAG (Q-DAG). Each…

cs.AI2014★ 30 cited

A Model-Based Active Testing Approach to Sequential Diagnosis

Alexander Feldman, Gregory Provan, Arjan van Gemund

Model-based diagnostic reasoning often leads to a large number of diagnostic hypotheses. The set of diagnoses can be reduced by taking into account extra observations (passive moni…

cs.AI2014★ 27 cited

Approximate Model-Based Diagnosis Using Greedy Stochastic Search

Alexander Feldman, Gregory Provan, Arjan van Gemund

We propose a StochAstic Fault diagnosis AlgoRIthm, called SAFARI, which trades off guarantees of computing minimal diagnoses for computational efficiency. We empirically demonstrat…

cs.AI2013★ 3 cited

A Logical Interpretation of Dempster-Shafer Theory, with Application to Visual Recognition

Gregory M. Provan

We formulate Dempster Shafer Belief functions in terms of Propositional Logic using the implicit notion of provability underlying Dempster Shafer Theory. Given a set of proposition…

cs.AI2013★ 1 cited

What is an Optimal Diagnosis?

David L. Poole, Gregory M. Provan

Within diagnostic reasoning there have been a number of proposed definitions of a diagnosis, and thus of the most likely diagnosis, including most probable posterior hypothesis, mo…

cs.AI2013

Dynamic Network Updating Techniques For Diagnostic Reasoning

Gregory M. Provan

A new probabilistic network construction system, DYNASTY, is proposed for diagnostic reasoning given variables whose probabilities change over time. Diagnostic reasoning is formula…