Optimal solutions to Markov Decision Problems (MDPs) are very sensitive with respect to the state transition probabilities. In many practical problems, the estimation of those pro...
Nowadays, the vast volume of collected digital data obliges us to employ processing methods like pattern recognition and data mining in order to reduce the complexity of data manag...
Ilaria Bartolini, Elisa Bertino, Barbara Catania, ...
The Multiagent Planning Architecture (MPA) is a framework for integrating diverse technologies into a system capable of solving complex planning problems. Agents within MPA share ...
We argue that some of the computational complexity associated with estimation of stochastic attributevalue grammars can be reduced by training upon an informative subset of the fu...
In this paper we present techniques for the real-time simulation and rendering of liquids. Appropriate approximations to a full 3D simulation are applied to reduce the numerical c...
Thomas Klein, Mike Eissele, Daniel Weiskopf, Thoma...