A dynamic epistemic framework for reasoning about conformant probabilistic plans

Yanjun Li, Barteld Kooi*, Yanjing Wang

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)
47 Downloads (Pure)


In this paper, we introduce a probabilistic dynamic epistemic logical framework that can be applied for reasoning and verifying conformant probabilistic plans in a single agent setting. In conformant probabilistic planning (CPP), we are looking for a linear plan such that the probability of achieving the goal after executing the plan is no less than a given threshold probability δ. Our logical framework can trace the change of the belief state of the agent during the execution of the plan and verify the conformant plans. Moreover, with this logic, we can enrich the CPP framework by formulating the goal as a formula in our language with action modalities and probabilistic beliefs. As for the main technical results, we provide a complete axiomatization of the logic and show the decidability of its validity problem.
Original languageEnglish
Pages (from-to)54-84
Number of pages31
JournalArtificial Intelligence
Early online date7-Dec-2018
Publication statusPublished - Mar-2019


  • Conformant probabilistic planning
  • Dynamic epistemic logic

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