Learning the reward function of an agent by observing its behavior is termed inverse reinforcement learning and has applications in learning from demonstration or apprenticeship l...
Abstract-- We study the convergence rate of average consensus algorithms in networks with stochastic communication failures. We show how the system dynamics can be modeled by a dis...
— This paper is about high capacity switches and routers that give guaranteed throughput, rate and delay guarantees. Many routers are built using input queueing or combined input...
This paper develops and evaluates new share-based scheduling algorithms for differentiated service quality in network services, such as network storage servers. This form of resou...
Computational grids offer users a simple access to tremendous computer resources for solving large scale computing problems. Traditional performance analysis of scheduling algorit...