The assessment of behavioral rules with respect to a given dataset is key in several research areas, including declarative process mining, association rule mining, and specification mining. An assessment is required to check how well a set of discovered rules describes the input data, and to...
01a Articolo in rivista
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In this paper we study instance-level update in DL-LiteA , a well-known description logic that influenced the OWL 2 QL standard. Instance-level update regards insertions and deletions in the ABox of an ontology. In particular we focus on formula-based approaches to instance-level update. We show...
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We present an iterative approach for planning and controlling motions of underactuated robots with uncertain dynamics. At its core, there is a learning process which estimates the perturbations induced by the model uncertainty on the active and passive degrees of freedom. The generic iteration of...
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The intrinsically underactuated and nonlinear nature of continuum soft robots makes the derivation of provably stable feedback control laws a challenging task. Most of the works so far circumvented the issue either by looking at coarse fully-actuated approximations of the dynamics or by imposing...
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The Covid-19 pandemic is forcing a rethink in robotics. In the form it is known today, robotics was prerogative of a broad community of insiders. But now, in the wreckage left behind by the coronavirus pandemic, a new era is beginning. What does it hold? In front of the crisis, more and more people...
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In this paper, we focus on the linear functionals defining an approximate version of the gradient of a function. These functionals are often used when dealing with optimization problems where the computation of the gradient of the objective function is costly or the objective function values are...
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Accurate modeling of the patient flow within an Emergency Department (ED) is required by all studies dealing with the increasing and well-known problem of overcrowding. Since Discrete Event Simulation (DES) models are often adopted with the aim of assessing solutions for reducing the impact of this...
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Decision-making in a complex, dynamic, interconnected, and data-intensive industrial environment can be improved with the assistance of machine-learning techniques. In this work, a complex instance of industrial assembly line control is formalized and a parallel deep reinforcement learning approach...
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This paper presents a novel control system for the participation of plug-in electric vehicles (PEVs) in the provisioning of ancillary services for frequency regulation, in a way that is transparent to the driver and harmonized with the smart charging service requirements. Given a power-frequency...