mlsanityData to 14 Oct 2026

Data-Driven Model Discrimination of Switched Nonlinear Systems with Temporal Logic Inference

arXiv 2306.09966 ↗First posted 16 Jun 2023cs.AIcited by 0

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Abstract (arXiv)

This paper addresses the problem of data-driven model discrimination for unknown switched systems with unknown linear temporal logic (LTL) specifications, representing tasks, that govern their mode sequences, where only sampled data of the unknown dynamics and tasks are available. To tackle this problem, we propose data-driven methods to over-approximate the unknown dynamics and to infer the unknown specifications such that both set-membership models of the unknown dynamics and LTL formulas are guaranteed to include the ground truth model and specification/task. Moreover, we present an optimization-based algorithm for analyzing the distinguishability of a set of learned/inferred model-task pairs as well as a model discrimination algorithm for ruling out model-task pairs from this set that are inconsistent with new observations at run time. Further, we present an approach for reducing the size of inferred specifications to increase the computational efficiency of the model discrimination algorithms.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 13 of its 81 references that are in the map. First posted on arXiv 16 Jun 2023.

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References · 13

  1. 2018Learning Linear Temporal Propertiescited by 41
  2. 2020Interpretable Sequence Classification via Discrete Optimizationcited by 19
  3. 2017Interpretable Apprenticeship Learning with Temporal Logic Specificationscited by 13
  4. 2018Information-Guided Temporal Logic Inference with Prior Knowledgecited by 13
  5. 2022Learning Interpretable Temporal Properties from Positive Examples Onlycited by 12
  6. 2021Learning Linear Temporal Properties from Noisy Data: A MaxSAT Approachcited by 11
  7. 2016Census Signal Temporal Logic Inference for Multi-Agent Group Behavior Analysiscited by 6
  8. 2019Graph Temporal Logic Inference for Classification and Identificationcited by 6
  9. 2016Guaranteed Model-Based Fault Detection in Cyber-Physical Systems: A Model Invalidation Approachcited by 2
  10. 2018Mesh-Based Affine Abstraction of Nonlinear Systems with Tighter Boundscited by 2
  11. 2020Data-Driven Model Invalidation for Unknown Lipschitz Continuous Systems via Abstractioncited by 2
  12. 2016Observability and diagnosability of finite state systems: a unifying frameworkcited by 1
1 more
  1. 2017Guaranteed Fault Detection and Isolation for Switched Affine Modelscited by 1

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