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20122026
most citedA Generally Applicable, Highly Scalable Measurement Computation and Optimization Approach to Sequential Model-Based Diagnosis

12 citations · 21 across the 8 of their papers we have counts for

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8 papers · 1 filter

cs.AI20203 cited

DynamicHS: Streamlining Reiter's Hitting-Set Tree for Sequential Diagnosis

Patrick Rodler

Given a system that does not work as expected, Sequential Diagnosis (SD) aims at suggesting a series of system measurements to isolate the true explanation for the system's misbeha…

cs.AI2019

Towards Optimizing Reiter's HS-Tree for Sequential Diagnosis

Patrick Rodler

Reiter's HS-Tree is one of the most popular diagnostic search algorithms due to its desirable properties and general applicability. In sequential diagnosis, where the addressed dia…

cs.AI201712 cited

A Generally Applicable, Highly Scalable Measurement Computation and Optimization Approach to Sequential Model-Based Diagnosis

Patrick Rodler, Wolfgang Schmid, Konstantin Schekotihin

Model-Based Diagnosis deals with the identification of the real cause of a system's malfunction based on a formal system model and observations of the system behavior. When a malfu…

cs.AI2017

Inexpensive Cost-Optimized Measurement Proposal for Sequential Model-Based Diagnosis

Patrick Rodler, Wolfgang Schmid, Konstantin Schekotihin

In this work we present strategies for (optimal) measurement selection in model-based sequential diagnosis. In particular, assuming a set of leading diagnoses being given, we show…

cs.AI2016

Interactive Debugging of Knowledge Bases

Patrick Rodler

Many AI applications rely on knowledge about a relevant real-world domain that is encoded by means of some logical knowledge base (KB). The most essential benefit of logical KBs is…

cs.AI2013

RIO: Minimizing User Interaction in Debugging of Knowledge Bases

Patrick Rodler, Kostyantyn Shchekotykhin, Philipp Fleiss +1

The best currently known interactive debugging systems rely upon some meta-information in terms of fault probabilities in order to improve their efficiency. However, misleading met…