Modern object-oriented programs are hierarchical systems with many thousands of interrelated subsystems. Visualization helps developers to better comprehend these large and comple...
Michael Balzer, Andreas Noack, Oliver Deussen, Cla...
We present a bottom-up parsing algorithm for stochastic context-free grammars that is able (1) to deal with multiple interpretations of sentences containing compoundwords; (2) to ...
Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
Reinforcement learning addresses the problem of learning to select actions in order to maximize one's performance inunknownenvironments. Toscale reinforcement learning to com...
We present a new algorithm that can be used for solving the model−checking problem for linear−time temporal logic. This algorithm can be viewed as the combination of two exist...