Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
—We consider a widely applicable model of resource allocation where two sequences of events are coupled: on a continuous time axis (t), network dynamics evolve over time. On a di...
Alexandre Proutiere, Yung Yi, Tian Lan, Mung Chian...
We consider distributed opportunistic scheduling (DOS) in wireless ad-hoc networks, where many links contend for the same channel using random access. In such networks, distribute...
The application of reinforcement learning algorithms to Partially Observable Stochastic Games (POSG) is challenging since each agent does not have access to the whole state inform...
Alessandro Lazaric, Mario Quaresimale, Marcello Re...
We consider a wireless collision channel, shared by a finite number of mobile users who transmit to a common base station using a random access protocol. Mobiles are selfoptimizin...