Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in largescale systems. In this work, we develop an organization-b...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
Sequence matching techniques are effective for comparing two videos. However, existing approaches suffer from demanding computational costs and thus are not scalable for large-sca...
In this abstract, we present a rule-based modelling language for constraint programming, called Rules2CP [1], and a library PKML for modelling packing problems. Unlike other modell...
Abstract. The PROBADO project is a research effort to develop Digital Library support for non-textual documents. The main goal is to contribute to all parts of the Digital Library...
Abstract. Ontology matching has become an important field of research over the last years. Although many different approaches have been proposed, only few of them are committed t...