A Logic for Default Reasoning About Probabilities

02/27/2013
by   Manfred Jaeger, et al.
0

A logic is defined that allows to express information about statistical probabilities and about degrees of belief in specific propositions. By interpreting the two types of probabilities in one common probability space, the semantics given are well suited to model the influence of statistical information on the formation of subjective beliefs. Cross entropy minimization is a key element in these semantics, the use of which is justified by showing that the resulting logic exhibits some very reasonable properties.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/27/2013

Generating New Beliefs From Old

In previous work [BGHK92, BGHK93], we have studied the random-worlds app...
research
09/03/2023

Logic of subjective probability

In this paper I discuss both syntax and semantics of subjective probabil...
research
03/13/2013

Empirical Probabilities in Monadic Deductive Databases

We address the problem of supporting empirical probabilities in monadic ...
research
07/22/2019

Learning Probabilities: Towards a Logic of Statistical Learning

We propose a new model for forming beliefs and learning about unknown pr...
research
09/26/2013

Reasoning about Probabilities in Dynamic Systems using Goal Regression

Reasoning about degrees of belief in uncertain dynamic worlds is fundame...
research
06/08/2023

Statistical relational learning and neuro-symbolic AI: what does first-order logic offer?

In this paper, our aim is to briefly survey and articulate the logical a...
research
03/27/2013

Assessment, Criticism and Improvement of Imprecise Subjective Probabilities for a Medical Expert System

Three paediatric cardiologists assessed nearly 1000 imprecise subjective...

Please sign up or login with your details

Forgot password? Click here to reset