Reasoning about knowledge and conditional probability

Sejla Dautovic; Dragan Doder; Zoran Ognjanovic

doi:10.1016/j.ijar.2023.109037

Reasoning about knowledge and conditional probability

Sejla Dautovic^*, Dragan Doder, Zoran Ognjanovic^*

^*Corresponding author for this work

Sub Intelligent Systems

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

We present a proof-theoretical and model-theoretical approach to reasoning about knowledge and conditional probability. We extend both the language of epistemic logic and the language of linear weight formulas, allowing statements like “Agent Ag knows that the probability of A given B is at least a half”. We present both a propositional and a first-order version of the logic. We provide sound and complete axiomatizations for both logics and we prove decidability in the propositional case.

Original language	English
Article number	109037
Pages (from-to)	1-16
Number of pages	16
Journal	International Journal of Approximate Reasoning
Volume	163
Early online date	25 Sept 2023
DOIs	https://doi.org/10.1016/j.ijar.2023.109037
Publication status	Published - Dec 2023

Bibliographical note

Publisher Copyright:
© 2023

Keywords

Probabilistic logic
Epistemic logic
Completeness theorem
Decidability

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10.1016/j.ijar.2023.109037

1-s2.0-S0888613X23001688-mainFinal published version, 686 KBLicence: Taverne

Cite this

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KW - Completeness theorem

KW - Decidability

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Reasoning about knowledge and conditional probability

Abstract

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Keywords

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