We present an objective approach for evaluating probability elicitation methods in probabilistic models. Our method draws on ideas from research on learning Bayesian networks: if ...
Although many real-world stochastic planning problems are more naturally formulated by hybrid models with both discrete and continuous variables, current state-of-the-art methods ...
Carlos Guestrin, Milos Hauskrecht, Branislav Kveto...
For mobile robots to assist people in everyday life, they must be easy to instruct. This paper describes a gesture-based interface for human robot interaction, which enables peopl...
Stefan Waldherr, Sebastian Thrun, Roseli Romero, D...
As the logical next step after sequencing the mouse genome, biologists have developed laboratory methods for rapidly determining where each of the 30K genes in the mouse genome is...
Joe D. Warren, Tao Ju, Gregor Eichele, Christina T...
We describe in this paper a new method for extracting knowledge on Hierarchical Task-Network (HTN) planning problems for speeding up the search. This knowledge is gathered by prop...