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Related papers: A quantum dynamic belief decision making model

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One of the most complex systems is the human brain whose formalized functioning is characterized by decision theory. We present a "Quantum Decision Theory" of decision making, based on the mathematical theory of separable Hilbert spaces.…

Artificial Intelligence · Computer Science 2010-10-29 V. I. Yukalov , D. Sornette

How should we model an observer within quantum mechanics or quantum field theory? How can classical physics emerge from a quantum model, and why should classical probability be useful? How can we model a selective measurement entirely…

Quantum Physics · Physics 2024-12-09 Brett Parker

We first show that there are practical situations in for instance forensic and gambling settings, in which applying classical probability theory, that is, based on the axioms of Kolmogorov, is problematic. We then introduce and discuss…

Probability · Mathematics 2015-12-07 Timber Kerkvliet , Ronald Meester

We present a general theory of quantum information processing devices, that can be applied to human decision makers, to atomic multimode registers, or to molecular high-spin registers. Our quantum decision theory is a generalization of the…

Quantum Physics · Physics 2009-11-13 V. I. Yukalov , D. Sornette

When we merge information in Dempster-Shafer Theory (DST), we are faced with anomalous behavior: agents with equal expertise and credibility can have their opinion disregarded after resorting to the belief combination rule of this theory.…

Artificial Intelligence · Computer Science 2024-08-20 Francisco Aragão , João Alcântara

An approach is presented treating decision theory as a probabilistic theory based on quantum techniques. Accurate definitions are given and thorough analysis is accomplished for the quantum probabilities describing the choice between…

Artificial Intelligence · Computer Science 2022-06-06 V. I. Yukalov

We present a novel variant of decision making based on the mathematical theory of separable Hilbert spaces. This mathematical structure captures the effect of superposition of composite prospects, including many incorporated intentions,…

Mathematical Physics · Physics 2011-03-07 V. I. Yukalov , D. Sornette

We analyse an argument of Deutsch, which purports to show that the deterministic part of classical quantum theory together with deterministic axioms of classical decision theory, together imply that a rational decision maker behaves as if…

Quantum Physics · Physics 2007-05-23 Richard D. Gill

In Dempster-Shafer belief theory, general beliefs are expressed as belief mass distribution functions over frames of discernment. In Subjective Logic beliefs are expressed as belief mass distribution functions over binary frames of…

Artificial Intelligence · Computer Science 2007-05-23 Audun Josang

The paper presents a novel view of the Dempster-Shafer belief function as a measure of diversity in relational data bases. It is demonstrated that under the interpretation The Dempster rule of evidence combination corresponds to the join…

Artificial Intelligence · Computer Science 2017-04-11 Mieczysław A. Kłopotek , Sławomir T. Wierzchoń

In the canonical examples underlying Shafer-Dempster theory, beliefs over the hypotheses of interest are derived from a probability model for a set of auxiliary hypotheses. Beliefs are derived via a compatibility relation connecting the…

Artificial Intelligence · Computer Science 2013-04-11 Kathryn Blackmond Laskey

We present a new experiment demonstrating destructive interference in customers' estimates of conditional probabilities of product failure. We take the perspective of a manufacturer of consumer products, and consider two situations of cause…

Artificial Intelligence · Computer Science 2022-06-01 Irina Basieva , Vijitashwa Pandey , Polina Khrennikova

The problem of combining beliefs in the Dempster-Shafer belief theory has attracted considerable attention over the last two decades. The classical Dempster's Rule has often been criticised, and many alternative rules for belief combination…

Artificial Intelligence · Computer Science 2007-05-23 Audun Josang

Human agents happen to judge that a conjunction of two terms is more probable than one of the terms, in contradiction with the rules of classical probabilities---this is the conjunction fallacy. One of the most discussed accounts of this…

Physics and Society · Physics 2016-06-15 Thomas Boyer-Kassem , Sébastien Duchêne , Eric Guerci

Approaches to decision-making under uncertainty in the belief function framework are reviewed. Most methods are shown to blend criteria for decision under ignorance with the maximum expected utility principle of Bayesian decision theory. A…

Artificial Intelligence · Computer Science 2019-12-13 Thierry Denoeux

Efficient modeling of uncertain information in real world is still an open issue. Dempster-Shafer evidence theory is one of the most commonly used methods. However, the Dempster-Shafer evidence theory has the assumption that the hypothesis…

Artificial Intelligence · Computer Science 2014-05-14 Yong Deng

We live in a world brimming with uncertainty, where we constantly have to make a lot of decisions under incomplete information. We are firm believers that our subjective belief cannot be computed by rigorous mathematical formula; instead…

Physics and Society · Physics 2023-02-08 Lizhi Xin , Kevin Xin , Houwen Xin

That superpositions of states can be useful for performing tasks in quantum systems has been known since the early days of quantum information, but only recently has quantitative theory of quantum coherence been proposed. Here we apply that…

Quantum Physics · Physics 2016-02-16 Mark Hillery

This paper describes a natural framework for rules, based on belief functions, which includes a repre- sentation of numerical rules, default rules and rules allowing and rules not allowing contraposition. In particular it justifies the use…

Artificial Intelligence · Computer Science 2013-04-05 Nic Wilson

This paper will focus on the process of 'fusing' several observations or models of uncertainty into a single resultant model. Many existing approaches to fusion use subjective quantities such as 'strengths of belief' and process these…

Artificial Intelligence · Computer Science 2020-07-28 Shawn C. Eastwood , Svetlana N. Yanushkevich