One of the major weaknesses of current research on the Semantic Web (SW) is the lack of proper means to represent and reason with uncertainty. A number of recent efforts from the ...
Paulo Cesar G. da Costa, Marcelo Ladeira, Rommel N...
To learn to behave in highly complex domains, agents must represent and learn compact models of the world dynamics. In this paper, we present an algorithm for learning probabilist...
Hanna Pasula, Luke S. Zettlemoyer, Leslie Pack Kae...
This paper investigates the combination of spatial and probabilistic models for reasoning about pedestrian behaviour in visual surveillance systems. Models are learnt by a multi-s...
We define strong monads of continuous (lower, upper) previsions, and of forks, modeling both probabilistic and non-deterministic choice. This is an elegant alternative to recent p...
We present a new on-line scheme for the recognition and pose estimation of a large isolated 3-D object, which may not entirely fit in a camera's field of view. We do not assu...