Log In Sign Up

A Decision Calculus for Belief Functions in Valuation-Based Systems

by   Hong Xu, et al.

Valuation-based system (VBS) provides a general framework for representing knowledge and drawing inferences under uncertainty. Recent studies have shown that the semantics of VBS can represent and solve Bayesian decision problems (Shenoy, 1991a). The purpose of this paper is to propose a decision calculus for Dempster-Shafer (D-S) theory in the framework of VBS. The proposed calculus uses a weighting factor whose role is similar to the probabilistic interpretation of an assumption that disambiguates decision problems represented with belief functions (Strat 1990). It will be shown that with the presented calculus, if the decision problems are represented in the valuation network properly, we can solve the problems by using fusion algorithm (Shenoy 1991a). It will also be shown the presented decision calculus can be reduced to the calculus for Bayesian probability theory when probabilities, instead of belief functions, are given.


page 1

page 2

page 3

page 4

page 5

page 6

page 7


Curry-Howard-Lambek Correspondence for Intuitionistic Belief

This paper introduces a natural deduction calculus for intuitionistic lo...

Making Decisions with Belief Functions

A primary motivation for reasoning under uncertainty is to derive decisi...

Anthropic decision theory

This paper sets out to resolve how agents ought to act in the Sleeping B...

Assessing forensic evidence by computing belief functions

We first discuss certain problems with the classical probabilistic appro...

Query Optimization Properties of Modified VBS

Valuation-Based System can represent knowledge in different domains incl...

The Role of Calculi in Uncertain Inference Systems

Much of the controversy about methods for automated decision making has ...

On Transformations between Probability and Spohnian Disbelief Functions

In this paper, we analyze the relationship between probability and Spohn...