Dependency networks are a compelling alternative to Bayesian networks for learning joint probability distributions from data and using them to compute probabilities. A dependency ...
As personal assistant software matures and assumes more autonomous control of its users’ activities, it becomes more critical that this software can explain its task processing....
Deborah L. McGuinness, Alyssa Glass, Michael Wolve...
Certain observable features (tags), shared by a group of similar agents, can be used to signal intentions and can be effectively used to infer unobservable properties. Such infere...
This paper details an essential component of a multi-agent distributed knowledge network system for intrusion detection. We describe a distributed intrusion detection architecture...
Guy G. Helmer, Johnny S. Wong, Vasant Honavar, Les...
—Most virtual reality simulators are designed for complex medical procedures, such as laparoscopic surgery. While important, these simulators are of use for only a subset of spec...
Nader S. Raja, John A. Schleser, William P. Norman...