Multiple-Phased Systems, whose operational life can be partitioned in a set of disjoint periods, called “phases”, include several classes of systems such as Phased Mission Sys...
Andrea Bondavalli, Ivan Mura, Silvano Chiaradonna,...
In this work we extend the work of Dean, Kaelbling, Kirman and Nicholson on planning under time constraints in stochastic domains to handle more complicated scheduling problems. I...
In this paper, we introduce a new approach to adaptive coding which utilizes Stochastic Learning-based Weak Estimation (SLWE) techniques to adaptively update the probabilities of t...
State-dependent importance sampling (SDIS) has proved to be particularly useful in simulation (specially in rare event analysis of stochastic systems). One approach for designing ...
Approximate dynamic programming is emerging as a powerful tool for certain classes of multistage stochastic, dynamic problems that arise in operations research. It has been applie...