Abstract. We present a possibly great improvement while performing semisupervised learning tasks from training data sets when only a small fraction of the data pairs is labeled. In...
Abstract. This paper calls on activity theory as tool for analyzing Asynchronous Learning Networks (ALN) to achieve a better understanding of their dynamics. This paper makes some ...
Abstract. We use a Markov Chain Monte Carlo (MCMC) MML algorithm to learn hybrid Bayesian networks from observational data. Hybrid networks represent local structure, using conditi...
Abstract. In this paper we utilize information theory to study the impact in learning performance of various motivation and environmental configurations. This study is done within...
Several concerns in the development of multi-agent systems (MASs) cannot be represented in a modular fashion. In general, they inherently affect several system modules and cannot b...