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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).

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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}
}

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The Complexity of Learning LTL, CTL and ATL Formulas

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