—Current industrial applications demand the design of more and more complex, safe and trustworthy control systems which exhibit a high degree of flexibility and reutilization. To...
Elisabet Estevez, Isabel Sarachaga, Federico Perez...
In this paper, we propose a new context-sensitive Bayesian learning algorithm. By modeling the distributions of data locations by a mixture of Gaussians, the new algorithm can uti...
Statistical analysis of bug discovery data is used in the software industry to check the quality of the testing process and estimate the reliability of the tested program. In this...
In this paper we propose a new distributed learning method called distributed network boosting (DNB) algorithm for distributed applications. The learned hypotheses are exchanged b...
This paper suggests an evolutionary approach to design coordination strategies, a key issue in distributed intelligent systems. We focus on competitive strategies in the form of f...