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We present AKR, a model checking tool for an adaptative probabilistic knowing-how epistemic logic. The tool takes as input the specification of a scenario modeled via a probabilistic LTS (in PRISM notation), a collection of regular expressions acting as agent’s perception, a knowing-how property, and checks whether the formula holds in the model under the given perception. The tool combines automata-based techniques with calls to the PRISM tool to compute the result. AKR is a publicly available, open-source tool entirely programmed in Python. We describe the tool’s architecture and illustrate its use via some examples.

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AKR: A Model Checker for an Adaptative Probabilistic Knowing-How Logic

  • 会议论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年

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  • Valentin Cassano,
  • Pablo F. Castro,
  • Pedro R. D’ Argenio,
  • Raul Fervari

摘要

We present AKR, a model checking tool for an adaptative probabilistic knowing-how epistemic logic. The tool takes as input the specification of a scenario modeled via a probabilistic LTS (in PRISM notation), a collection of regular expressions acting as agent’s perception, a knowing-how property, and checks whether the formula holds in the model under the given perception. The tool combines automata-based techniques with calls to the PRISM tool to compute the result. AKR is a publicly available, open-source tool entirely programmed in Python. We describe the tool’s architecture and illustrate its use via some examples.