Counter-example guided Imitation Learning of Feedback Controllers from Temporal Logic Specifications
<|reference_start|>Counter-example guided Imitation Learning of Feedback Controllers from Temporal Logic Specifications: We present a novel method for imitation learning for control requirements expressed using Signal Temporal Logic (STL). More concretely we focus on the problem of training a neural network to imitate a complex controller. The learning process is guided by efficient data aggregation based on counter-examples and a coverage measure. Moreover, we introduce a method to evaluate the performance of the learned controller via parameterization and parameter estimation of the STL requirements. We demonstrate our approach with a flying robot case study.<|reference_end|>
@article{dang2024counter-example,
    title={Counter-example guided Imitation Learning of Feedback Controllers from
  Temporal Logic Specifications},
    author={Thao Dang, Alexandre Donz'e, Inzemamul Haque, Nikolaos Kekatos, and
  Indranil Saha},
    journal={arXiv preprint arXiv:2403.16593},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.16593},
    primaryClass={cs.RO cs.SY eess.SY}
}