Continuous-time Markov decision processes (MDPs), also known as controlled Markov chains, are used for modeling decision-making problems that arise in operations research (for instance, inventory, manufacturing, and queueing systems), computer scien
an update formula that allows the expression of the deviation matrix of a continuous-time Markov process with denumerable state space having generator matrix through a continuous-time Markov process with generator matrix Q. We show that under suitab
The automatic generation of decision trees based on off-line reasoning on models of a domain is a reasonable compromise between the advantages of using a model-based approach in technical domains and the constraints imposed by embedded applications.
