Automata Learning meets Shielding

Martin Tappler, Stefan Pranger, Bettina Könighofer, Edi Muskardin, Roderick Bloem, Kim Guldstrand Larsen

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem KonferenzbandBegutachtung


Safety is still one of the major research challenges in reinforcement learning (RL). In this paper, we address the problem of how to avoid safety violations of RL agents during exploration in probabilistic and partially unknown environments. Our approach combines automata learning for Markov Decision Processes (MDPs) and shield synthesis in an iterative approach. Initially, the MDP representing the environment is unknown. The agent starts exploring the environment and collects traces. From the collected traces, we passively learn MDPs that abstractly represent the safety-relevant aspects of the environment. Given a learned MDP and a safety specification, we construct a shield. For each state-action pair within a learned MDP, the shield computes exact probabilities on how likely it is that executing the action results in violating the specification from the current state within the next k steps. After the shield is constructed, the shield is used during runtime and blocks any actions that induce a too large risk from the agent. The shielded agent continues to explore the environment and collects new data on the environment. Iteratively, we use the collected data to learn new MDPs with higher accuracy, resulting in turn in shields able to prevent more safety violations. We implemented our approach and present a detailed case study of a Q-learning agent exploring slippery Gridworlds. In our experiments, we show that as the agent explores more and more of the environment during training, the improved learned models lead to shields that are able to prevent many safety violations.
TitelLeveraging Applications of Formal Methods, Verification and Validation. Verification Principles - 11th International Symposium, ISoLA 2022, Proceedings
UntertitelISoLA 2022
Redakteure/-innenTiziana Margaria, Bernhard Steffen
Herausgeber (Verlag)Springer
ISBN (elektronisch)978-3-031-19849-6
ISBN (Print)978-3-031-19848-9
PublikationsstatusVeröffentlicht - 2022
VeranstaltungISOLA 2022: 11th International Symposium On Leveraging Applications of Formal Methods, Verification and Validation - Rhodos, Griechenland
Dauer: 22 Okt. 202230 Okt. 2022


NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band13701 LNCS
ISSN (Print)0302-9743
ISSN (elektronisch)1611-3349


KonferenzISOLA 2022
KurztitelISOLA 2022


  • Automata Learning
  • Markov Decision Processes
  • Shielding

ASJC Scopus subject areas

  • Theoretische Informatik
  • Allgemeine Computerwissenschaft


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