Verification of reachability properties for probabilistic systems is usually based on variants of Markov processes. Current methods assume an exact model of the dynamic behavior a...
The Markov Blanket of a target variable is the minimum conditioning set of variables that makes the target independent of all other variables. Markov Blankets inform feature selec...
Lewis Frey, Douglas H. Fisher, Ioannis Tsamardinos...
Markov decision processes are an effective tool in modeling decision-making in uncertain dynamic environments. Since the parameters of these models are typically estimated from da...
Typically, Markov decision problems (MDPs) assume a single action is executed per decision epoch, but in the real world one may frequently execute certain actions in parallel. Thi...
Despite the significant progress to extend Markov Decision Processes (MDP) to cooperative multi-agent systems, developing approaches that can deal with realistic problems remains ...