In this paper we study the identification of sparse interaction networks as a machine learning problem. Sparsity means that we are provided with a small data set and a high number...
Goele Hollanders, Geert Jan Bex, Marc Gyssens, Ron...
Programming in an open environment remains challenging because it requires combining modularity, security, concurrency, distribution, and dynamicity. In this paper, we propose an ...
Michael Lienhardt, Alan Schmitt, Jean-Bernard Stef...
Wireless Mesh Networks with static Transit Access Points (TAPs) have many advantages to connect different kinds of networks. While Mobile Ad hoc Networks still have many challenges...
Learning Classifier Systems use evolutionary algorithms to facilitate rule- discovery, where rule fitness is traditionally payoff based and assigned under a sharing scheme. Most c...
Abstract. In this paper we present a novel general framework for encoding and evolving networks called Common Genetic Encoding (CGE) that can be applied to both direct and indirect...
Yohannes Kassahun, Jan Hendrik Metzen, Jose de Gea...