It is well known that among all probabilistic graphical Markov models the class of decomposable models is the most advantageous in the sense that the respective distributions can b...
Partially Observable Markov Decision Processes (POMDP) provide a standard framework for sequential decision making in stochastic environments. In this setting, an agent takes actio...
We define an abstract model of belief propagation on a graph based on the methodology of the revision theory of truth together with the Assertion Network Toolkit, a graphical inter...
With the increasing popularity of largescale probabilistic graphical models, even "lightweight" approximate inference methods are becoming infeasible. Fortunately, often...
Since knowledge bases (KBs) are usually incomplete, they should be able to provide information regarding their own incompleteness, which requires them to introspect on what they k...