I introduce a temporal belief-network representation of causal independence that a knowledge engineer can use to elicit probabilistic models. Like the current, atemporal belief-ne...
We used a new method to assess how people can infer unobserved causal structure from patterns of observed events. Participants were taught to draw causal graphs, and then shown a ...
Tamar Kushnir, Alison Gopnik, Chris Lucas, Laura S...
Flexible and effective indexing of video data so as to render it useful in automated inference and datadriven knowledge acquisition is a key problem in knowledge engineering. In t...
Jie Bao, Yu Cao, Wallapak Tavanapong, Vasant Honav...
Bayesiannetworks provide a languagefor qualitatively representing the conditional independence properties of a distribution. This allows a natural and compact representation of th...
Designing electronic markets is still a rather intricate process. eNegotiation - and thereby trading rules - embody the core of the institution ”electronic market”. Although s...