This paper explores the relationship between routine-biased technological change and agglomeration economies. Using administrative data from Netherlands, we first show that in dense areas, jobs are less routine-task intensive (i.e. repetitive automatable), meaning cover a larger spectrum of tasks. We then explore how routine intensity affects urban wage premium. find premium is higher for worke...

We present Bayesian Description Logics (BDLs): an extension of Description Logics (DLs) with contextual probabilities encoded in a Bayesian network (BN). Classical DL reasoning tasks are extended to consider also the contextual and probabilistic information in BDLs. A complexity analysis of these problems shows that, for propositionally closed DLs, this extension comes without cost, while for t...

This paper discusses a planner-based approach to automating data production tasks, such as producing fire forecasts from satellite imagery and weather station data. Since the set of available data products is large, dynamic and mostly unknown, planning techniques developed for closed worlds are unsuitable. We discuss a number of techniques we have developed to cope with data production domains,...

The construction of a closed-loop observer for linear control systems and the associated eigenvalue assignment problem are classical tasks in Control Theory. The present paper describes an algorithm for the solution of this eigenvalue assignment problem. The algorithm is based on the implicitly restarted Arnoldi method, and is well suited for large-scale problems, that require the (re)assignmen...

A novel framework for interactive image registration is proposed. In this formulation, a closed loop system is created to control the PDE defining the registration evolution; a human expert user is present “in the loop” coupled with a convenient choice of automatic algorithm. The result is a system that leverages the expert’s high level anatomical knowledge with an automatic method’s speed in p...

In recent years, a large number of algorithms have been proposed for finding set patterns in boolean data. This includes popular mining tasks based on, for instance, frequent (closed) itemsets. In this chapter, we develop a common framework in which these algorithms can be studied thanks to the principles of constraint programming. We show how such principles can be applied both in specialized ...

In this paper a new class of sets called  regular generalized  $delta$-closed set (briefly rg$delta$-closed set)is introduced and its properties are studied. Several examples are provided to illustrate the behaviour of these new class of sets.