Partially Observable Markov Decision Process models (POMDPs) have been applied to low-level robot control. We show how to use POMDPs differently, namely for sensorplanning in the ...
Most probabilistic inference algorithms are specified and processed on a propositional level. In the last decade, many proposals for algorithms accepting first-order specificat...
The paper introduces mixed networks, a new framework for expressing and reasoning with probabilistic and deterministic information. The framework combines belief networks with con...
: The guarantee of feasibility given feasibility at initial time is an issue that has been overlooked by many of the recent papers on stochastic model predictive control. Effective...
Basil Kouvaritakis, Mark Cannon, Sasa V. Rakovic, ...
One problem in concatenative speech synthesis is how to incorporate prosodic factors in the unit selection. Imposing a predicted prosodic target is error-prone and does not benefi...