4 Search Results for "Wiener, Thomas"

Document
DOI: 10.4230/LIPIcs.COSIT.2024.5
Spatial Nudging: Converging Persuasive Technologies, Spatial Design, and Behavioral Theories

Authors: Ayda Grisiute and Martin Raubal

Published in: LIPIcs, Volume 315, 16th International Conference on Spatial Information Theory (COSIT 2024)

Abstract
This paper presents the Spatial Nudging framework - a theory-based framework that maps out nudging strategies in the mobility domain and refines its existing definitions. We link these strategies by highlighting the role of perceived affordances across physical and digital interventions based on the Nudge Theory and the Theory of Affordances. Furthermore, we propose to use graph representation techniques as a supportive methodology to better align perceived and actual environments, thereby enhancing the intervention strategies' effectiveness. We illustrate the applicability of the Spatial Nudging framework and the supportive methodology in the context of an E-bike City vision. This paper lays the foundation for future research on theoretically integrating physical and digital interventions to promote sustainable mobility.
Cite as

Ayda Grisiute and Martin Raubal. Spatial Nudging: Converging Persuasive Technologies, Spatial Design, and Behavioral Theories. In 16th International Conference on Spatial Information Theory (COSIT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 315, pp. 5:1-5:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{grisiute_et_al:LIPIcs.COSIT.2024.5,
  author =	{Grisiute, Ayda and Raubal, Martin},
  title =	{{Spatial Nudging: Converging Persuasive Technologies, Spatial Design, and Behavioral Theories}},
  booktitle =	{16th International Conference on Spatial Information Theory (COSIT 2024)},
  pages =	{5:1--5:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-330-0},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{315},
  editor =	{Adams, Benjamin and Griffin, Amy L. and Scheider, Simon and McKenzie, Grant},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2024.5},
  URN =		{urn:nbn:de:0030-drops-208206},
  doi =		{10.4230/LIPIcs.COSIT.2024.5},
  annote =	{Keywords: spatial nudging, active mobility, Nudge Theory, Theory of Affordances, cognitive graphs}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2023.21
Automata Learning with an Incomplete Teacher

Authors: Mark Moeller, Thomas Wiener, Alaia Solko-Breslin, Caleb Koch, Nate Foster, and Alexandra Silva

Published in: LIPIcs, Volume 263, 37th European Conference on Object-Oriented Programming (ECOOP 2023)

Abstract
The preceding decade has seen significant interest in use of active learning to build models of programs and protocols. But existing algorithms assume the existence of an idealized oracle - a so-called Minimally Adequate Teacher (MAT) - that cannot be fully realized in practice and so is usually approximated with testing. This work proposes a new framework for active learning based on an incomplete teacher. This new formulation, called iMAT, neatly handles scenarios in which the teacher has access to only a finite number of tests or otherwise has gaps in its knowledge. We adapt Angluin’s L^⋆ algorithm for learning finite automata to incomplete teachers and we build a prototype implementation in OCaml that uses an SMT solver to help fill in information not supplied by the teacher. We demonstrate the behavior of our iMAT prototype on a variety of learning problems from a standard benchmark suite.
Cite as

Mark Moeller, Thomas Wiener, Alaia Solko-Breslin, Caleb Koch, Nate Foster, and Alexandra Silva. Automata Learning with an Incomplete Teacher. In 37th European Conference on Object-Oriented Programming (ECOOP 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 263, pp. 21:1-21:30, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{moeller_et_al:LIPIcs.ECOOP.2023.21,
  author =	{Moeller, Mark and Wiener, Thomas and Solko-Breslin, Alaia and Koch, Caleb and Foster, Nate and Silva, Alexandra},
  title =	{{Automata Learning with an Incomplete Teacher}},
  booktitle =	{37th European Conference on Object-Oriented Programming (ECOOP 2023)},
  pages =	{21:1--21:30},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-281-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{263},
  editor =	{Ali, Karim and Salvaneschi, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2023.21},
  URN =		{urn:nbn:de:0030-drops-182145},
  doi =		{10.4230/LIPIcs.ECOOP.2023.21},
  annote =	{Keywords: Finite Automata, Active Learning, SMT Solvers}
}
Document
Artifact
DOI: 10.4230/DARTS.9.2.21
Automata Learning with an Incomplete Teacher (Artifact)

Authors: Mark Moeller, Thomas Wiener, Alaia Solko-Breslin, Caleb Koch, Nate Foster, and Alexandra Silva

Published in: DARTS, Volume 9, Issue 2, Special Issue of the 37th European Conference on Object-Oriented Programming (ECOOP 2023)

Abstract
We provide an implementation of the automata learning software described in the associated ECOOP article. In particular, the artifact is a Docker image with the source code for nerode and nerode-learn, along with the scripts and benchmark inputs needed to reproduce the experiments described in the paper.
Cite as

Mark Moeller, Thomas Wiener, Alaia Solko-Breslin, Caleb Koch, Nate Foster, and Alexandra Silva. Automata Learning with an Incomplete Teacher (Artifact). In Special Issue of the 37th European Conference on Object-Oriented Programming (ECOOP 2023). Dagstuhl Artifacts Series (DARTS), Volume 9, Issue 2, pp. 21:1-21:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{moeller_et_al:DARTS.9.2.21,
  author =	{Moeller, Mark and Wiener, Thomas and Solko-Breslin, Alaia and Koch, Caleb and Foster, Nate and Silva, Alexandra},
  title =	{{Automata Learning with an Incomplete Teacher (Artifact)}},
  pages =	{21:1--21:3},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2023},
  volume =	{9},
  number =	{2},
  editor =	{Moeller, Mark and Wiener, Thomas and Solko-Breslin, Alaia and Koch, Caleb and Foster, Nate and Silva, Alexandra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DARTS.9.2.21},
  URN =		{urn:nbn:de:0030-drops-182612},
  doi =		{10.4230/DARTS.9.2.21},
  annote =	{Keywords: Finite Automata, Active Learning, SMT Solvers}
}
Document
DOI: 10.4230/DagSemProc.04401.6
Lower Bounds and Non-Uniform Time Discretization for Approximation of Stochastic Heat Equations

Authors: Klaus Ritter and Thomas Müller-Gronbach

Published in: Dagstuhl Seminar Proceedings, Volume 4401, Algorithms and Complexity for Continuous Problems (2005)

Abstract
We study algorithms for approximation of the mild solution of stochastic heat equations on the spatial domain ]0,1[^d. The error of an algorithm is defined in L_2-sense. We derive lower bounds for the error of every algorithm that uses a total of N evaluations of one-dimensional components of the driving Wiener process W. For equations with additive noise we derive matching upper bounds and we construct asymptotically optimal algorithms. The error bounds depend on N and d, and on the decay of eigenvalues of the covariance of W in the case of nuclear noise. In the latter case the use of non-uniform time discretizations is crucial.
Cite as

Klaus Ritter and Thomas Müller-Gronbach. Lower Bounds and Non-Uniform Time Discretization for Approximation of Stochastic Heat Equations. In Algorithms and Complexity for Continuous Problems. Dagstuhl Seminar Proceedings, Volume 4401, pp. 1-37, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2005)

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@InProceedings{ritter_et_al:DagSemProc.04401.6,
  author =	{Ritter, Klaus and M\"{u}ller-Gronbach, Thomas},
  title =	{{Lower Bounds and Non-Uniform Time Discretization for Approximation of Stochastic Heat Equations}},
  booktitle =	{Algorithms and Complexity for Continuous Problems},
  pages =	{1--37},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2005},
  volume =	{4401},
  editor =	{Thomas M\"{u}ller-Gronbach and Erich Novak and Knut Petras and Joseph F. Traub},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.04401.6},
  URN =		{urn:nbn:de:0030-drops-1518},
  doi =		{10.4230/DagSemProc.04401.6},
  annote =	{Keywords: Stochastic heat equation , Non-uniform time discretization , minimal errors , upper and lower bounds}
}
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