Model-Based Diagnosis (MBD) typically focuses on diagnoses, minimal under some minimality criterion, e.g., the minimal-cardinality set of faulty components that explain an observa...
Alexander Feldman, Gregory M. Provan, Arjan J. C. ...
We present a general machine learning framework for modelling the phenomenon of missing information in data. We propose a masking process model to capture the stochastic nature of...
Intermittent failures and nondeterministic behavior complicate and compromise the effectiveness of software testing and debugging. To increase the observability of software faults,...
Raza Abbas Syed, Brian Robinson, Laurie A. William...
Partially observable Markov decision processes (POMDPs) provide a principled, general framework for robot motion planning in uncertain and dynamic environments. They have been app...
Sylvie C. W. Ong, Shao Wei Png, David Hsu, Wee Sun...
Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...