A Robust Genetic Algorithm for Learning Temporal Specifications from Data
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Abstract (arXiv)
We consider the problem of mining signal temporal logical requirements from a dataset of regular (good) and anomalous (bad) trajectories of a dynamical system. We assume the training set to be labeled by human experts and that we have access only to a limited amount of data, typically noisy. We provide a systematic approach to synthesize both the syntactical structure and the parameters of the temporal logic formula using a two-steps procedure: first, we leverage a novel evolutionary algorithm for learning the structure of the formula; second, we perform the parameter synthesis operating on the statistical emulation of the average robustness for a candidate formula w.r.t. its parameters. We compare our results with our previous work [{BufoBSBLB14] and with a recently proposed decision-tree [bombara_decision_2016] based method. We present experimental results on two case studies: an anomalous trajectory detection problem of a naval surveillance system and the characterization of an Ineffective Respiratory effort, showing the usefulness of our work.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Nov 2017.
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Citing papers per year: 2022: 1; 2023: 2; 2024: 3; 2025: 5.
11 papers.
- 2022Learning Model Checking and the Kernel Trick for Signal Temporal Logic on Stochastic Processescited by 7
- 2024Retrieval-Augmented Mining of Temporal Logic Specifications from Datacited by 5
- 2023Synthesizing Efficiently Monitorable Formulas in Metric Temporal Logiccited by 3
- 2024Learning Temporal Logic Predicates from Data with Statistical Guaranteescited by 2
- 2025Learning Probabilistic Temporal Logic Specifications for Stochastic Systemscited by 2
- 2023Joint Learning of Policy with Unknown Temporal Constraints for Safe Reinforcement Learningcited by 1
- 2024Concurrent Learning of Policy and Unknown Safety Constraints in Reinforcement Learningcited by 1
- 2025Bridging Logic and Learning: Decoding Temporal Logic Embeddings via Transformerscited by 1
- 2025Automata Learning of Preferences over Temporal Logic Formulas from Pairwise Comparisonscited by 0
- 2025Towards Interpretable Concept Learning over Time Series via Temporal Logic Semanticscited by 0
- 2025Guided by Stars: Interpretable Concept Learning Over Time Series via Temporal Logic Semanticscited by 0
- 2025Guided by Stars: Interpretable Concept Learning Over Time Series via Temporal Logic Semantics6 Nov 2025
- 2025Towards Interpretable Concept Learning over Time Series via Temporal Logic Semantics5 Aug 2025
- 2025Bridging Logic and Learning: Decoding Temporal Logic Embeddings via Transformers10 Jul 2025
- 2025Automata Learning of Preferences over Temporal Logic Formulas from Pairwise Comparisons23 May 2025
- 2025Learning Probabilistic Temporal Logic Specifications for Stochastic Systems17 May 2025
- 2024Learning Temporal Logic Predicates from Data with Statistical Guarantees15 Jun 2024
- 2024Retrieval-Augmented Mining of Temporal Logic Specifications from Data23 May 2024
- 2024Concurrent Learning of Policy and Unknown Safety Constraints in Reinforcement Learning24 Feb 2024
- 2023Synthesizing Efficiently Monitorable Formulas in Metric Temporal Logic26 Oct 2023
- 2023Joint Learning of Policy with Unknown Temporal Constraints for Safe Reinforcement Learning30 Apr 2023
- 2022Learning Model Checking and the Kernel Trick for Signal Temporal Logic on Stochastic Processes24 Jan 2022