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Imprecise Probability Models of Rational Belief

Project description

Developing imprecise probability models

Probability theory uses mathematical functions to determine the likelihood of various outcomes to a random event. In practice, it can help governments and businesses make rational decisions. However, if outcomes to an event have a high degree of uncertainty due to limited data, standard probability functions are insufficient. A typical example is trying to rationalise decisions concerning climate change. The MSCA-funded IPMRB project aims to develop sound models of rational belief based on imprecise probabilities by building on standard probability theory. The new models will make it possible for agents to reach decisions that more reliably reflect the limited data in cases of extreme uncertainty.

Objective

"Imprecise Probability Models of Rational Belief.

The goal of this project is to provide a philosophically well founded theory of rational belief based on ""Imprecise Probabilities""(IP). That is, instead of the orthodox Bayesian approach to modelling belief using probability functions, the IP approach uses a set of probability functions as the representation of belief. This promises to be a more foundationally secure, more normatively compelling, more descriptively accurate and more representationally powerful theory of rational belief. The project consists of three parts. The first analyses the basic concept of IP, and the methodology of formal epistemology more generally. The second explores learning and inference in an IP setting, and the third focusses on decision making with IP."

Fields of science (EuroSciVoc)

Programme(s)

Topic(s)

Funding Scheme

MSCA-IF-EF-ST - Standard EF

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Call for proposal

(opens in new window) H2020-MSCA-IF-2017

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Coordinator

UNIVERSITY OF LEEDS
Net EU contribution
€ 183 454,80
Address
WOODHOUSE LANE
LS2 9JT Leeds
United Kingdom
Region
Yorkshire and the Humber West Yorkshire Leeds
Activity type
Higher or Secondary Education Establishments
Links
Total cost
€ 183 454,80