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Found 7 papers, 2 papers with code
Specification-Driven Video Search via Foundation Models and Formal Verification
The increasing abundance of video data enables users to search for events of interest, e. g., emergency incidents.
Reinforcement Learning with Temporal-Logic-Based Causal Diagrams
We study a class of reinforcement learning (RL) tasks where the objective of the agent is to accomplish temporally extended goals.
Automaton-Based Representations of Task Knowledge from Generative Language Models
However, the textual outputs from GLMs cannot be formally verified or used for sequential decision-making.
Learning Temporal Logic Properties: an Overview of Two Recent Methods
Learning linear temporal logic (LTL) formulas from examples labeled as positive or negative has found applications in inferring descriptions of system behavior.
Learning Interpretable Temporal Properties from Positive Examples Only
To learn meaningful models from positive examples only, we design algorithms that rely on conciseness and language minimality of models as regularizers.
Uncertainty-Aware Signal Temporal Logic Inference
In this paper, we first investigate the uncertainties associated with trajectories of a system and represent such uncertainties in the form of interval trajectories.
Learning Linear Temporal Properties from Noisy Data: A MaxSAT Approach
Our first algorithm infers minimal LTL formulas by reducing the inference problem to a problem in maximum satisfiability and then using off-the-shelf MaxSAT solvers to find a solution.
