2 Search Results for "Ostrowski, Martin"


Document
Theory Solving Made Easy with Clingo 5

Authors: Martin Gebser, Roland Kaminski, Benjamin Kaufmann, Max Ostrowski, Torsten Schaub, and Philipp Wanko

Published in: OASIcs, Volume 52, Technical Communications of the 32nd International Conference on Logic Programming (ICLP 2016)


Abstract
Answer Set Programming (ASP) is a model, ground, and solve paradigm. The integration of application- or theory-specific reasoning into ASP systems thus impacts on many if not all elements of its workflow, viz. input language, grounding, intermediate language, solving, and output format. We address this challenge with the fifth generation of the ASP system clingo and its grounding and solving components by equipping them with well-defined generic interfaces facilitating the manifold integration efforts. On the grounder's side, we introduce a generic way of specifying language extensions and propose an intermediate format accommodating their ground representation. At the solver end, this is accompanied by high-level interfaces easing the integration of theory propagators dealing with these extensions.

Cite as

Martin Gebser, Roland Kaminski, Benjamin Kaufmann, Max Ostrowski, Torsten Schaub, and Philipp Wanko. Theory Solving Made Easy with Clingo 5. In Technical Communications of the 32nd International Conference on Logic Programming (ICLP 2016). Open Access Series in Informatics (OASIcs), Volume 52, pp. 2:1-2:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)


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@InProceedings{gebser_et_al:OASIcs.ICLP.2016.2,
  author =	{Gebser, Martin and Kaminski, Roland and Kaufmann, Benjamin and Ostrowski, Max and Schaub, Torsten and Wanko, Philipp},
  title =	{{Theory Solving Made Easy with Clingo 5}},
  booktitle =	{Technical Communications of the 32nd International Conference on Logic Programming (ICLP 2016)},
  pages =	{2:1--2:15},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-007-1},
  ISSN =	{2190-6807},
  year =	{2016},
  volume =	{52},
  editor =	{Carro, Manuel and King, Andy and Saeedloei, Neda and De Vos, Marina},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.ICLP.2016.2},
  URN =		{urn:nbn:de:0030-drops-67337},
  doi =		{10.4230/OASIcs.ICLP.2016.2},
  annote =	{Keywords: Answer Set Programming, Theory Language, Theory Propagation}
}
Document
Stochastic Delay Prediction in Large Train Networks

Authors: Annabell Berger, Andreas Gebhardt, Matthias Müller-Hannemann, and Martin Ostrowski

Published in: OASIcs, Volume 20, 11th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (2011)


Abstract
In daily operation, railway traffic always deviates from the planned schedule to a certain extent. Primary initial delays of trains may cause a whole cascade of secondary delays of other trains over the entire network. In this paper, we propose a stochastic model for delay propagation and forecasts of arrival and departure events which is applicable to all kind of public transport (not only to railway traffic). Our model is fairly realistic, it includes general waiting policies (how long do trains wait for delayed feeder trains), it uses driving time profiles (discrete distributions) on travel arcs which depend on the departure time, and it incorporates the catch-up potential of buffer times on driving sections and train stops. The model is suited for an online scenario where a massive stream of update messages on the current status of trains arrives which has to be propagated through the whole network. Efficient stochastic propagation of delays has important applications in online timetable information, in delay management and train disposition, and in stability analysis of timetables. The proposed approach has been implemented and evaluated on the German timetable of 2011 with waiting policies of Deutsche Bahn AG. A complete stochastic delay propagation for the whole German train network and a whole day can be performed in less than 14 seconds on a PC. We tested our propagation algorithm with artificial discrete travel time distributions which can be parametrized by the size of their fluctuations. Our forecasts are compared with real data. It turns out that stochastic propagation of delays is efficient enough to be applicable in practice, but the forecast quality requires further adjustments of our artificial travel time distributions to estimates from real data.

Cite as

Annabell Berger, Andreas Gebhardt, Matthias Müller-Hannemann, and Martin Ostrowski. Stochastic Delay Prediction in Large Train Networks. In 11th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems. Open Access Series in Informatics (OASIcs), Volume 20, pp. 100-111, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)


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@InProceedings{berger_et_al:OASIcs.ATMOS.2011.100,
  author =	{Berger, Annabell and Gebhardt, Andreas and M\"{u}ller-Hannemann, Matthias and Ostrowski, Martin},
  title =	{{Stochastic Delay Prediction in Large Train Networks}},
  booktitle =	{11th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems},
  pages =	{100--111},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-33-0},
  ISSN =	{2190-6807},
  year =	{2011},
  volume =	{20},
  editor =	{Caprara, Alberto and Kontogiannis, Spyros},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2011.100},
  URN =		{urn:nbn:de:0030-drops-32705},
  doi =		{10.4230/OASIcs.ATMOS.2011.100},
  annote =	{Keywords: stochastic delay propagation, timetable information, delay management, train disposition, stability analysis}
}
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