Reinforcement Learning research is traditionally devoted to solve single-task problems. Therefore, anytime a new task is faced, learning must be restarted from scratch. Recently, ...
Functional symmetries provide significant benefits for multiple tasks in synthesis and verification. Many applications require the manual specification of symmetries using spe...
Guoqiang Wang, Andreas Kuehlmann, Alberto L. Sangi...
In this study, we investigate the task scheduling problem in heterogeneous computing environments and propose a novel scheduling algorithm, called the Artificial Immune System wit...
This paper presents a new approach for mapping task graphs to heterogeneous hardware/software computing systems using heuristic search techniques. Two techniques: (1) integration ...
In this paper we study simple families of clustered graphs that are highly unconnected. We start by studying 3-cluster cycles, which are clustered graphs such that the underlying ...
Pier Francesco Cortese, Giuseppe Di Battista, Maur...