We present a model for buying agents in e-marketplaces to interpret evaluations of sellers provided by other buying agents, known as advisors. The interpretation of seller evaluat...
We present a noisy-OR Bayesian network model for simulation-based training, and an efficient search-based algorithm for automatic synthesis of plausible training scenarios from co...
Eugene Grois, William H. Hsu, Mikhail Voloshin, Da...
We consider multiple agents who's task is to determine the true state of a uncertain domain so they can act properly. If each agent only has partial knowledge about the domai...
Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, ...
—Deformable models have recently been proposed for many pattern recognition applications due to their ability to handle large shape variations.These proposed approaches represent...