Metrics for Signal Temporal Logic Formulae
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Abstract (arXiv)
Signal Temporal Logic (STL) is a formal language for describing a broad range of real-valued, temporal properties in cyber-physical systems. While there has been extensive research on verification and control synthesis from STL requirements, there is no formal framework for comparing two STL formulae. In this paper, we show that under mild assumptions, STL formulae admit a metric space. We propose two metrics over this space based on i) the Pompeiu-Hausdorff distance and ii) the symmetric difference measure, and present algorithms to compute them. Alongside illustrative examples, we present applications of these metrics for two fundamental problems: a) design quality measures: to compare all the temporal behaviors of a designed system, such as a synthetic genetic circuit, with the "desired" specification, and b) loss functions: to quantify errors in Temporal Logic Inference (TLI) as a first step to establish formal performance guarantees of TLI algorithms.
Key facts. Cited by 9 papers in the map (data through 13 Oct 2026). First posted on arXiv 1 Aug 2018.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 2; 2025: 4; 2026: 1.
9 papers.
- 2024Temporal Logic Specification-Conditioned Decision Transformer for Offline Safe Reinforcement Learningcited by 10
- 2025Enhancing Transformation from Natural Language to Signal Temporal Logic Using LLMs with Diverse External Knowledgecited by 9
- 2022Learning Model Checking and the Kernel Trick for Signal Temporal Logic on Stochastic Processescited by 7
- 2025Grammar-Forced Translation of Natural Language to Temporal Logic using LLMscited by 7
- 2021STL Robustness Risk over Discrete-Time Stochastic Processescited by 4
- 2025Verifiable Natural Language to Linear Temporal Logic Translation: A Benchmark Dataset and Evaluation Suitecited by 4
- 2024stl2vec: Semantic and Interpretable Vector Representation of Temporal Logiccited by 3
- 2026ClarifySTL: An Interactive LLM Agent Framework for STL Transformation through Requirements Clarificationcited by 2
- 2025SPoRt -- Safe Policy Ratio: Certified Training and Deployment of Task Policies in Model-Free RLcited by 1
- 2026ClarifySTL: An Interactive LLM Agent Framework for STL Transformation through Requirements Clarification2 May 2026
- 2025Grammar-Forced Translation of Natural Language to Temporal Logic using LLMs18 Dec 2025
- 2025Verifiable Natural Language to Linear Temporal Logic Translation: A Benchmark Dataset and Evaluation Suite1 Jul 2025
- 2025Enhancing Transformation from Natural Language to Signal Temporal Logic Using LLMs with Diverse External Knowledge27 May 2025
- 2025SPoRt -- Safe Policy Ratio: Certified Training and Deployment of Task Policies in Model-Free RL8 Apr 2025
- 2024stl2vec: Semantic and Interpretable Vector Representation of Temporal Logic23 May 2024
- 2024Temporal Logic Specification-Conditioned Decision Transformer for Offline Safe Reinforcement Learning27 Feb 2024
- 2022Learning Model Checking and the Kernel Trick for Signal Temporal Logic on Stochastic Processes24 Jan 2022
- 2021STL Robustness Risk over Discrete-Time Stochastic Processes3 Apr 2021