Solving probability puzzles with logic toolkit

05/18/2023
by   Adrian Groza, et al.
0

The proposed approach is to formalise the probabilistic puzzle in equational FOL. Two formalisations are needed: one theory for all models of the given puzzle, and a second theory for the favorable models. Then Mace4 - that computes all the interpretation models of a FOL theory - is called twice. First, it is asked to compute all the possible models M p .Second, the additional constraint is added, and Mace4 computes only favourabile models M f. Finally, the definition of probability is applied: the number of favorable models is divided by the number of possible models. The proposed approach equips students from the logic tribe to find the correct solution for puzzles from the probabilitistic tribe, by using their favourite instruments: modelling and formalisation. I have exemplified here five probabilistic puzzles and how they can be solved by translating the min FOL and then find the corresponding interpretation models. Mace4 was the tool of choice here. Ongoing work is investigating the limits of this method on various collections of probabilistic puzzles

READ FULL TEXT
research
04/06/2017

Transferrable Plausibility Model - A Probabilistic Interpretation of Mathematical Theory of Evidence

This paper suggests a new interpretation of the Dempster-Shafer theory i...
research
01/31/2022

A Sampling-Aware Interpretation of Linear Logic: Syntax and Categorical Semantics

The usual resource interpretation of linear logic says that variables ha...
research
03/27/2013

Summary of A New Normative Theory of Probabilistic Logic

By probabilistic logic I mean a normative theory of belief that explains...
research
03/27/2013

Some Extensions of Probabilistic Logic

In [12], Nilsson proposed the probabilistic logic in which the truth val...
research
03/27/2013

A Measure-Free Approach to Conditioning

In an earlier paper, a new theory of measurefree "conditional" objects w...
research
05/09/2012

Constraint Processing in Lifted Probabilistic Inference

First-order probabilistic models combine representational power of first...
research
03/27/2013

Can Uncertainty Management be Realized in a Finite Totally Ordered Probability Algebra?

In this paper, the feasibility of using finite totally ordered probabili...

Please sign up or login with your details

Forgot password? Click here to reset