Universal induction solves in principle the problem of choosing a prior to achieve optimal inductive inference. The AIXI theory, which combines control theory and universal induct...
Next to prediction accuracy, the interpretability of models is one of the fundamental criteria for machine learning algorithms. While high accuracy learners have intensively been e...
This paper presents a tool for MPLS network dimensioning that allows for multi-hour dimensioning of networks supporting simultaneously peer-to-peer and client-server services. The...
GraphPlan-like and SATPLAN-like planners have shown to outperform classical planners for most of the classical planning domains. However, these two propositional approaches do not ...
We present a theory of a modeler's problem decomposition skills in the context of optimal reasonzng -- the use of qualitative modeling to strategically guide numerical explor...