Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
The Hepar II system is based on a Bayesian network model of a subset of the domain of hepatology in which the structure of the network is elicited from an expert diagnostician and ...
A new class of data structures called "bumptrees" is described. These structures are useful for efficiently implementing a number of neural network related operations. A...
— We present an analytic and geometric view of the sample mean of graphs. The theoretical framework yields efficient subgradient methods for approximating a structural mean and ...
We present an approach to keyhole plan recognition which uses a dynamic belief (Bayesian) network to represent features of the domain that are needed to identify users’ plans and...
David W. Albrecht, Ingrid Zukerman, Ann E. Nichols...