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, ...
We address distributed real-time applications represented by systems of non-preemptive dependent periodic tasks. This system is described by an acyclic directed graph. Because the...
The Universum data, defined as a collection of "nonexamples" that do not belong to any class of interest, have been shown to encode some prior knowledge by representing ...
Dan Zhang, Jingdong Wang, Fei Wang, Changshui Zhan...
Abstract. In the context of an approach for reengineering legacy software systems at the architectural level, we present in this paper a reverse engineering methodology that uses a...
Rui Correia, Carlos M. P. Matos, Mohammad El-Ramly...
This paper presents an investigation of a simple generic hyper-heuristic approach upon a set of widely used constructive heuristics (graph coloring heuristics) in timetabling. Wit...
Edmund K. Burke, Barry McCollum, Amnon Meisels, Sa...