Sampling has become an important strategy for inference in belief networks. It can also be applied to the problem of selecting actions in influence diagrams. In this paper, we pre...
Although commonly used in both commercial and experimental information retrieval systems, thesauri have not demonstrated consistent bene ts for retrieval performance, and it is di...
We propose a new method to program robots based on Bayesian inference and learning. It is called BRP for Bayesian Robot Programming. The capacities of this programming method are d...
Theefficiency of algorithmsfor probabilistic inference in Bayesian networks can be improvedby exploiting independenceof causal influence. Thefactorized representation of independe...
—This paper proposes a probabilistic technique that enables a node to estimate the number of its neighbors that fulfill certain criteria. The technique does not require any a pr...
Helmut Adam, Evsen Yanmaz, Wilfried Elmenreich, Ch...