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Documents authored by Neider, Daniel

Document
DOI: 10.4230/LIPIcs.ICDT.2025.24
Learning Tree Pattern Transformations

Authors: Daniel Neider, Leif Sabellek, Johannes Schmidt, Fabian Vehlken, and Thomas Zeume

Published in: LIPIcs, Volume 328, 28th International Conference on Database Theory (ICDT 2025)

Abstract
Explaining why and how a tree t structurally differs from another tree t^⋆ is a question that is encountered throughout computer science, including in understanding tree-structured data such as XML or JSON data. In this article, we explore how to learn explanations for structural differences between pairs of trees from sample data: suppose we are given a set {(t₁, t₁^⋆),… , (t_n, t_n^⋆)} of pairs of labelled, ordered trees; is there a small set of rules that explains the structural differences between all pairs (t_i, t_i^⋆)? This raises two research questions: (i) what is a good notion of "rule" in this context?; and (ii) how can sets of rules explaining a data set be learned algorithmically? We explore these questions from the perspective of database theory by (1) introducing a pattern-based specification language for tree transformations; (2) exploring the computational complexity of variants of the above algorithmic problem, e.g. showing NP-hardness for very restricted variants; and (3) discussing how to solve the problem for data from CS education research using SAT solvers.
Cite as

Daniel Neider, Leif Sabellek, Johannes Schmidt, Fabian Vehlken, and Thomas Zeume. Learning Tree Pattern Transformations. In 28th International Conference on Database Theory (ICDT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 328, pp. 24:1-24:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{neider_et_al:LIPIcs.ICDT.2025.24,
  author =	{Neider, Daniel and Sabellek, Leif and Schmidt, Johannes and Vehlken, Fabian and Zeume, Thomas},
  title =	{{Learning Tree Pattern Transformations}},
  booktitle =	{28th International Conference on Database Theory (ICDT 2025)},
  pages =	{24:1--24:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-364-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{328},
  editor =	{Roy, Sudeepa and Kara, Ahmet},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2025.24},
  URN =		{urn:nbn:de:0030-drops-229652},
  doi =		{10.4230/LIPIcs.ICDT.2025.24},
  annote =	{Keywords: Tree pattern transformations, learning from positive examples, computational complexity}
}
Document
DOI: 10.4230/LIPIcs.STACS.2025.19
The Complexity of Learning LTL, CTL and ATL Formulas

Authors: Benjamin Bordais, Daniel Neider, and Rajarshi Roy

Published in: LIPIcs, Volume 327, 42nd International Symposium on Theoretical Aspects of Computer Science (STACS 2025)

Abstract
We consider the problem of learning temporal logic formulas from examples of system behavior. Learning temporal properties has crystallized as an effective means to explain complex temporal behaviors. Several efficient algorithms have been designed for learning temporal formulas. However, the theoretical understanding of the complexity of the learning decision problems remains largely unexplored. To address this, we study the complexity of the passive learning problems of three prominent temporal logics, Linear Temporal Logic (LTL), Computation Tree Logic (CTL) and Alternating-time Temporal Logic (ATL) and several of their fragments. We show that learning formulas with unbounded occurrences of binary operators is NP-complete for all of these logics. On the other hand, when investigating the complexity of learning formulas with bounded occurrences of binary operators, we exhibit discrepancies between the complexity of learning LTL, CTL and ATL formulas (with a varying number of agents).
Cite as

Benjamin Bordais, Daniel Neider, and Rajarshi Roy. The Complexity of Learning LTL, CTL and ATL Formulas. In 42nd International Symposium on Theoretical Aspects of Computer Science (STACS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 327, pp. 19:1-19:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{bordais_et_al:LIPIcs.STACS.2025.19,
  author =	{Bordais, Benjamin and Neider, Daniel and Roy, Rajarshi},
  title =	{{The Complexity of Learning LTL, CTL and ATL Formulas}},
  booktitle =	{42nd International Symposium on Theoretical Aspects of Computer Science (STACS 2025)},
  pages =	{19:1--19:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-365-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{327},
  editor =	{Beyersdorff, Olaf and Pilipczuk, Micha{\l} and Pimentel, Elaine and Thắng, Nguy\~{ê}n Kim},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2025.19},
  URN =		{urn:nbn:de:0030-drops-228441},
  doi =		{10.4230/LIPIcs.STACS.2025.19},
  annote =	{Keywords: Temporal logic, passive learning, complexity}
}
Document
DOI: 10.4230/LIPIcs.MFCS.2020.74
Optimally Resilient Strategies in Pushdown Safety Games

Authors: Daniel Neider, Patrick Totzke, and Martin Zimmermann

Published in: LIPIcs, Volume 170, 45th International Symposium on Mathematical Foundations of Computer Science (MFCS 2020)

Abstract
Infinite-duration games with disturbances extend the classical framework of infinite-duration games, which captures the reactive synthesis problem, with a discrete measure of resilience against non-antagonistic external influence. This concerns events where the observed system behavior differs from the intended one prescribed by the controller. For games played on finite arenas it is known that computing optimally resilient strategies only incurs a polynomial overhead over solving classical games. This paper studies safety games with disturbances played on infinite arenas induced by pushdown systems. We show how to compute optimally resilient strategies in triply-exponential time. For the subclass of safety games played on one-counter configuration graphs, we show that determining the degree of resilience of the initial configuration is PSPACE-complete and that optimally resilient strategies can be computed in doubly-exponential time.
Cite as

Daniel Neider, Patrick Totzke, and Martin Zimmermann. Optimally Resilient Strategies in Pushdown Safety Games. In 45th International Symposium on Mathematical Foundations of Computer Science (MFCS 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 170, pp. 74:1-74:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{neider_et_al:LIPIcs.MFCS.2020.74,
  author =	{Neider, Daniel and Totzke, Patrick and Zimmermann, Martin},
  title =	{{Optimally Resilient Strategies in Pushdown Safety Games}},
  booktitle =	{45th International Symposium on Mathematical Foundations of Computer Science (MFCS 2020)},
  pages =	{74:1--74:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-159-7},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{170},
  editor =	{Esparza, Javier and Kr\'{a}l', Daniel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.MFCS.2020.74},
  URN =		{urn:nbn:de:0030-drops-127432},
  doi =		{10.4230/LIPIcs.MFCS.2020.74},
  annote =	{Keywords: Controller Synthesis, Infinite Games, Resilient Strategies, Pushdown Games}
}
Document
DOI: 10.4230/DagRep.9.9.1
Logic and Learning (Dagstuhl Seminar 19361)

Authors: Michael Benedikt, Kristian Kersting, Phokion G. Kolaitis, and Daniel Neider

Published in: Dagstuhl Reports, Volume 9, Issue 9 (2020)

Abstract
The goal of building truly intelligent systems has forever been a central problem in computer science. While logic-based approaches of yore have had their successes and failures, the era of machine learning, specifically deep learning is also coming upon significant challenges. There is a growing consensus that the inductive reasoning and complex, high-dimensional pattern recognition capabilities of deep learning models need to be combined with symbolic (even programmatic), deductive capabilities traditionally developed in the logic and automated reasoning communities in order to achieve the next step towards building intelligent systems, including making progress at the frontier of hard problems such as explainable AI. However, these communities tend to be quite separate and interact only minimally, often at odds with each other upon the subject of the ``correct approach'' to AI. This report documents the efforts of Dagstuhl Seminar 19361 on ``Logic and Learning'' to bring these communities together in order to: (i) bridge the research efforts between them and foster an exchange of ideas in order to create unified formalisms and approaches that bear the advantages of both research methodologies; (ii) review and analyse the progress made across both communities; (iii) understand the subtleties and difficulties involved in solving hard problems using both perspectives; (iv) make attempts towards a consensus on what the hard problems are and what the elements of good solutions to these problems would be. The three focal points of the seminar were the strands of ``Logic for Machine Learning'', ``Machine Learning for Logic'', and ``Logic vs. Machine Learning''. The seminar format consisted of long and short talks, as well as breakout sessions. We summarise the motivations and proceedings of the seminar, and report on the abstracts of the talks and the results of the breakout sessions.
Cite as

Michael Benedikt, Kristian Kersting, Phokion G. Kolaitis, and Daniel Neider. Logic and Learning (Dagstuhl Seminar 19361). In Dagstuhl Reports, Volume 9, Issue 9, pp. 1-22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@Article{benedikt_et_al:DagRep.9.9.1,
  author =	{Benedikt, Michael and Kersting, Kristian and Kolaitis, Phokion G. and Neider, Daniel},
  title =	{{Logic and Learning (Dagstuhl Seminar 19361)}},
  pages =	{1--22},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2020},
  volume =	{9},
  number =	{9},
  editor =	{Benedikt, Michael and Kersting, Kristian and Kolaitis, Phokion G. and Neider, Daniel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.9.9.1},
  URN =		{urn:nbn:de:0030-drops-118425},
  doi =		{10.4230/DagRep.9.9.1},
  annote =	{Keywords: Artificial Intelligence, Automated reasoning, Databases, Deep Learning, Inductive Logic Programming, Logic, Logic and Learning, Logic for Machine Learning, Logic vs. Machine Learning, Machine Learning, Machine Learning for Logic, Neurosymbolic methods}
}
Document
DOI: 10.4230/LIPIcs.CSL.2018.34
Synthesizing Optimally Resilient Controllers

Authors: Daniel Neider, Alexander Weinert, and Martin Zimmermann

Published in: LIPIcs, Volume 119, 27th EACSL Annual Conference on Computer Science Logic (CSL 2018)

Abstract
Recently, Dallal, Neider, and Tabuada studied a generalization of the classical game-theoretic model used in program synthesis, which additionally accounts for unmodeled intermittent disturbances. In this extended framework, one is interested in computing optimally resilient strategies, i.e., strategies that are resilient against as many disturbances as possible. Dallal, Neider, and Tabuada showed how to compute such strategies for safety specifications. In this work, we compute optimally resilient strategies for a much wider range of winning conditions and show that they do not require more memory than winning strategies in the classical model. Our algorithms only have a polynomial overhead in comparison to the ones computing winning strategies. In particular, for parity conditions optimally resilient strategies are positional and can be computed in quasipolynomial time.
Cite as

Daniel Neider, Alexander Weinert, and Martin Zimmermann. Synthesizing Optimally Resilient Controllers. In 27th EACSL Annual Conference on Computer Science Logic (CSL 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 119, pp. 34:1-34:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{neider_et_al:LIPIcs.CSL.2018.34,
  author =	{Neider, Daniel and Weinert, Alexander and Zimmermann, Martin},
  title =	{{Synthesizing Optimally Resilient Controllers}},
  booktitle =	{27th EACSL Annual Conference on Computer Science Logic (CSL 2018)},
  pages =	{34:1--34:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-088-0},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{119},
  editor =	{Ghica, Dan R. and Jung, Achim},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CSL.2018.34},
  URN =		{urn:nbn:de:0030-drops-97010},
  doi =		{10.4230/LIPIcs.CSL.2018.34},
  annote =	{Keywords: Controller Synthesis, Infinite Games, Resilient Strategies, Disturbances}
}
Document
DOI: 10.4230/LIPIcs.CSL.2016.10
Robust Linear Temporal Logic

Authors: Paulo Tabuada and Daniel Neider

Published in: LIPIcs, Volume 62, 25th EACSL Annual Conference on Computer Science Logic (CSL 2016)

Abstract
Although it is widely accepted that every system should be robust, in the sense that "small" violations of environment assumptions should lead to "small" violations of system guarantees, it is less clear how to make this intuitive notion of robustness mathematically precise. In this paper, we address the problem of how to specify robustness in temporal logic. Our solution consists of a robust version of the Linear Temporal Logic (LTL) fragment that only contains the always and eventually temporal operators.
Cite as

Paulo Tabuada and Daniel Neider. Robust Linear Temporal Logic. In 25th EACSL Annual Conference on Computer Science Logic (CSL 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 62, pp. 10:1-10:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@InProceedings{tabuada_et_al:LIPIcs.CSL.2016.10,
  author =	{Tabuada, Paulo and Neider, Daniel},
  title =	{{Robust Linear Temporal Logic}},
  booktitle =	{25th EACSL Annual Conference on Computer Science Logic (CSL 2016)},
  pages =	{10:1--10:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-022-4},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{62},
  editor =	{Talbot, Jean-Marc and Regnier, Laurent},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CSL.2016.10},
  URN =		{urn:nbn:de:0030-drops-65508},
  doi =		{10.4230/LIPIcs.CSL.2016.10},
  annote =	{Keywords: Linear Temporal Logic, Robustness}
}
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