The number of distributed high performance computing architectures has increased exponentially these last years. Thus, systems composed by several computational resources provided ...
Program dynamic optimization, adaptive to runtime behavior changes, has become increasingly important for both performance and energy savings. However, most runtime optimizations o...
This paper is about Reinforcement Learning (RL) applied to online parameter tuning in Stochastic Local Search (SLS) methods. In particular a novel application of RL is considered i...
We take institutions seriously as both a rational response to dilemmas in which agents found themselves and a frame to which later rational agents adapted their behaviour in turn....
In this paper we consider the problem of maximising utility in linked market-driven distributed and Grid systems. In such systems, users submit jobs through brokers who can virtua...