We show how a generic feature selection algorithm returning strongly relevant variables can be turned into a causal structure learning algorithm. We prove this under the Faithfuln...
We consider the problem of assembling concurrent software systems from untrusted or partially trusted o -the-shelf components, using wrapper programs to encapsulate components and...
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...
We study syntax-free models for name-passing processes. For interleaving semantics, we identify the indexing structure required of an early labelled transition system to support t...
We describe a system for specifying the effects of actions. Unlike those commonly used in AI planning, our system uses an action description language that allows one to specify th...