In this paper, we present an adaptive model for dynamically deforming hyper-elastic rods. In contrast to existing approaches, adaptively introduced control points are not governed...
The increased complexity, heterogeneity and the dynamism of networked systems and services make current control and management tools to be ineffective in managing and securing suc...
We propose a modular reinforcement learning architecture for non-linear, nonstationary control tasks, which we call multiple model-based reinforcement learning (MMRL). The basic i...
Designing and organising large numbers of autonomic resources into a coherent system is a difficult endeavour. It necessitates handling complex interactions among dynamic, heteroge...
— A significant impediment to deployment of multicast services is the daunting technical complexity of developing, testing and validating congestion control protocols fit for w...