on models are abstract representations of systems one wants to study through computer simulation. In multiagent based simulation, such models usually represent agents and their re...
Multi-instance (MI) learning is a variant of supervised learning where labeled examples consist of bags (i.e. multi-sets) of feature vectors instead of just a single feature vecto...
In this paper we present a new approach to derive heavy-traffic asymptotics for polling models. We consider the classical cyclic polling model with exhaustive or gated service at ...
Recent advances in functional Magnetic Resonance Imaging (fMRI) offer a significant new approach to studying semantic representations in humans by making it possible to directly o...
Kai-min K. Chang, Vladimir Cherkassky, Tom M. Mitc...
The constraint paradigm provides powerful concepts to represent and solve different kinds of planning problems, e. g. factory scheduling. Factory scheduling is a demanding optimiz...