L*-Based Learning of Markov Decision Processes (Extended Version)

@article{Tappler2021LBasedLO,
  title={L*-Based Learning of Markov Decision Processes (Extended Version)},
  author={Martin Tappler and Bernhard K. Aichernig and Giovanni Bacci and Maria Eichlseder and Kim Guldstrand Larsen},
  journal={Formal Aspects Comput.},
  year={2021},
  volume={33},
  pages={575-615}
}
Automata learning techniques automatically generate systemmodels fromtest observations. Typically, these techniques fall into two categories: passive and active. On the one hand, passive learning assumes no interaction with the system under learning and uses a predetermined training set, e.g., system logs. On the other hand, active learning techniques collect training data by actively querying the system under learning, allowing one to steer the discovery ofmeaningful information about the… 
2 Citations
L*-Based Learning of Markov Decision Processes
TLDR
This paper focuses on automata learning techniques, which automatically generate system models from test observations and actively queries the system under learning, which is considered more efficient.

References

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