We consider approximate policy evaluation for finite state and action Markov decision processes (MDP) in the off-policy learning context and with the simulation-based least square...
This paper deals with a category of concavifiable functions that can be used to model inelastic traffic in the network. Such class of functions can be concavified within an interva...
Resource limited DRE (Distributed Real-time Embedded) systems can benefit greatly from dynamic adaptation of system parameters. We propose a novel approach that employs iterative t...
Minyoung Kim, Mark-Oliver Stehr, Carolyn L. Talcot...
Access control in decentralised collaborative systems present huge challenges especially where many autonomous entities including organisations, humans, software agents from diff...
Oluwafemi Ajayi, Richard O. Sinnott, Anthony Stell
We address the problem of optimally controlling stochastic environments that are partially observable. The standard method for tackling such problems is to define and solve a Part...