Planning under uncertainty involves two distinct sources of uncertainty: uncertainty about the effects of actions and uncertainty about the current state of the world. The most wi...
Deterministic optimization approaches have been well developed and widely used in the process industry to accomplish off-line and on-line process optimization. The challenging tas...
In distributed stream processing environments, large numbers of continuous queries are distributed onto multiple servers. When one or more of these servers become overloaded due t...
One of the difficulties to adapt MDPs for the control of cooperative multi-agent systems, is the complexity issued from Decentralized MDPs. Moreover, existing approaches can not ...
A Markov Decision Process (MDP) is a general model for solving planning problems under uncertainty. It has been extended to multiobjective MDP to address multicriteria or multiagen...