A central problem in qualitative reasoning is understanding how people reason about space and shape with diagrams. We claim that progress in diagrammatic reasoning is being slowed...
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...
This paper demonstrates qualitative spatial reasoning techniques in a real-world diagrammatic reasoning task: Course-of-Action (COA) diagrams. COA diagrams are military planning d...
Ronald W. Ferguson, Robert A. Rasch Jr., William T...
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...
We describe a general approach to optimization which we term Squeaky Wheel" Optimization SWO. In SWO, a greedy algorithm is used to construct a solution which is then analyze...