Bayesian networks are probabilistic graphical models widely employed in AI for the implementation of knowledge-based systems. Standard inference algorithms can update the beliefs a...
—As sensor networks are finding widespread use across many applications, designers increasingly must not only focus on application development, but also on sensor network optimiz...
Jeff Hiner, Ashish Shenoy, Roman L. Lysecky, Susan...
Abstract. In this paper, we propose a Bayesian network-based trust model in peerto-peer networks. Since trust is multi-faceted, even in the same context, peers still need to develo...
Neurodynamical models of working memory (WM) should provide mechanisms for storing, maintaining, retrieving, and deleting information. Many models address only a subset of these a...
Credal networks are models that extend Bayesian nets to deal with imprecision in probability, and can actually be regarded as sets of Bayesian nets. Credal nets appear to be power...