Dynamic Probability Logic: Decidability & Computability
Somayeh Chopoghloo, Mahdi Heidarpoor, Massoud Pourmahdian
TL;DR
This paper investigates the decidability and computability of dynamic probability logic (DPL), introducing proof systems that establish its logical properties and computational aspects.
Contribution
It presents two proof systems for DPL, proving weak and strong completeness, and demonstrates that DPL is decidable with a computable canonical model.
Findings
DPL has a weakly complete proof system
DPL possesses the finite model property and is decidable
The canonical model of DPL is a computable structure
Abstract
In this article, the decidability and computability issues of dynamic probability logic (DPL) are addressed. Firstly, a proof system is introduced for DPL and shown that it is weakly complete. Furthermore, this logic has the finite model property and so is decidable. Secondly, a strongly complete proof system HDPL is presented for DPL and proved that its canonical model is a computable structure.
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Taxonomy
TopicsLogic, Reasoning, and Knowledge · Bayesian Modeling and Causal Inference · Advanced Database Systems and Queries