Genetic algorithms (GAs) are stochastic search methods that have been successfully applied in many search, optimization, and machine learning problems. Their parallel counterpart (...
Resource performance in the Computational Grid is not only heterogeneous, but also changing dynamically. However scheduling algorithms designed for traditional parallel and distri...
Efficient task scheduling is critical to achieving high performance on grid computing environment. A heuristic task scheduling algorithm satisfied resources load balancing on grid ...
This paper introduces the RL-TOPs architecture for robot learning, a hybrid system combining teleo-reactive planning and reinforcement learning techniques. The aim of this system ...
In this paper, we present a checkpoint-based scheme to improve the turnaround time of bag-of-tasks applications executed on institutional desktop grids. We propose to share checkp...