To provide an opportunity for students to experiment with probabilistic models and reasoning methods, in order to better understand the workings and limitations of these methods. This class is highly recommended as a supplementary course to the VO "Probabilistic Models", where the theoretical foundations are explained.
Subject
Practical experiments with probabilistic models. Development of simple systems that model and reason about some given problem. Specific focus: (discrete) Bayes Nets and temporal models (Hidden Markov Models, Kalman Filter).
Criteria for evaluation
Independent experimenting based on given problem specifications. Written and/or oral report on the results.
