Many real datasets have uncertain categorical attribute values that are only approximately measured or imputed. Uncertainty in categorical data is commonplace in many applications...
Self-explaining has been repeatedly shown to result in positive learning outcomes for students in a wide variety of disciplines. However, there are two potential accounts for why s...
In this work, we propose two high-level formalisms, Markov Decision Petri Nets (MDPNs) and Markov Decision Well-formed Nets (MDWNs), useful for the modeling and analysis of distrib...
Marco Beccuti, Giuliana Franceschinis, Serge Hadda...
I present MOSES (meta-optimizing semantic evolutionary search), a new probabilistic modeling (estimation of distribution) approach to program evolution. Distributions are not esti...
Within many domains, among which biological and cognitive areas, multiple interacting processes occur among agents with dynamics that are hard to handle. Current approaches to ana...
Tibor Bosse, Catholijn M. Jonker, Lourens van der ...