We propose a new approach to the problem of searching a space of policies for a Markov decision process (MDP) or a partially observable Markov decision process (POMDP), given a mo...
In this work, we propose two high-level formalisms, Markov Decision Petri Nets (MDPNs) and Markov Decision Well-formed Nets (MDWNs), useful for the modeling and analysis of distrib...
Marco Beccuti, Giuliana Franceschinis, Serge Hadda...
We consider the fundamental problem of monitoring (i.e. tracking) the belief state in a dynamic system, when the model is only approximately correct and when the initial belief st...
Existing algorithms for discrete partially observable Markov decision processes can at best solve problems of a few thousand states due to two important sources of intractability:...
We design opportunistic spectrum access strategies for improving spectrum efficiency. In each slot, a secondary user chooses a subset of channels to sense and decides whether to ac...