A fundamental question in causal inference is whether it is possible to reliably infer the manipulation effects from observational data. There are a variety of senses of asymptot...
Previous studies have demonstrated that encoding a Bayesian network into a SAT-CNF formula and then performing weighted model counting using a backtracking search algorithm can be...
We consider the problem of incorporating arbitrary preferences in planning systems. A preference may be seen as a goal or constraint that is desirable, but not necessary, to satis...
Queries for composite events typically involve the four complementary dimensions of event data, event composition, relationships between events (esp. temporal and causal), and acc...
We propose to extend the temporal causal graph formalisms used in model-based diagnosis in order to deal with non trivial interactions like (partial) cancellation of fault effects...