A central problem in learning in complex environmentsis balancing exploration of untested actions against exploitation of actions that are known to be good. The benefit of explora...
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...
The "minimum margin" of an ensemble classifier on a given training set is, roughly speaking, the smallest vote it gives to any correct training label. Recent work has sh...
Despite much research that has been done on constraint satisfaction problems (CSP's), the framework is sometimes inflexible and the results are not very satisfactory when app...
Modifyingknowledge-based systems is a complexactivity. One of its di culties is that several related portions of the system might have to be changed in order to maintain the coher...