We consider sensor scheduling as the optimal observability problem for partially observable Markov decision processes (POMDP). This model fits to the cases where a Markov process ...
We present a method for specifying temporal constraints on trajectories of dynamical systems and enforcing them during qualitative simulation. This capability can be used to focus...
Abstract—Many application domains require adaptive realtime embedded systems that can change their functionality over time. In such systems it is not only necessary to guarantee ...
Nikolay Stoimenov, Simon Perathoner, Lothar Thiele
In the future, webs of unmanned air and space vehicles will act together to robustly perform elaborate missions in uncertain environments. We coordinate these systems by introduci...
Abstract. An optimal probabilistic-planning algorithm solves a problem, usually modeled by a Markov decision process, by finding its optimal policy. In this paper, we study the k ...