Identifying user-dependent information that can be automatically collected helps build a user model by which 1) to predict what the user wants to do next and 2) to do relevant pre...
Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, ...
Functionality-based recognition systems recognize objects at the category level by reasoning about how well the objects support the expected function. Such systems naturally assoc...
We design a representation based on the situation calculus to facilitate development, maintenance and elaboration of very large taxonomies of actions. This representation leads to...
Approaches to reasoning about knowledge in imperfect information games typically involve an exhaustive description of the game, the dynamics characterized by a tree and the incomp...