Active learning aims to reduce the amount of labels required for classification. The main difficulty is to find a good trade-off between exploration and exploitation of the lab...
The Partially Observable Markov Decision Process (POMDP) model is explored for high level decision making for Unmanned Air Vehicles (UAVs). The type of UAV modeled is a flying mun...
We present a vision based, adaptive, decision theoretic model of human facial displays in interactions. The model is a partially observable Markov decision process, or POMDP. A POM...
Several algorithms for learning near-optimal policies in Markov Decision Processes have been analyzed and proven efficient. Empirical results have suggested that Model-based Inter...
This paper investigates relative precision and optimality of analyses for concurrent probabilistic systems. Aiming at the problem at the heart of probabilistic model checking ? com...