MAXIMAL CONSISTENCY, THEORY OF EVIDENCE, AND BAYESIAN CONDITIONING IN THE INVESTIGATIVE DOMAIN

2003 ◽  
Vol 34 (6-7) ◽  
pp. 419-465 ◽  
Author(s):  
ALDO FRANCO DRAGONI ◽  
SAMUELE ANIMALI
Keyword(s):  
Consistency Theory ◽  
Theory Of Evidence ◽  
Bayesian Conditioning

Cognitive Consistency Theory in Social Psychology: A Paradigm Reconsidered

2017 ◽  
Author(s):  
Arie W. Kruglanski ◽  
Katarzyna Jasko ◽  
Maxim Milyavsky ◽  
Marina Chernikova ◽  
David Webber ◽  
...  
Keyword(s):  
Social Psychology ◽  
Negative Affect ◽  
Affective Responses ◽  
Cognitive Consistency ◽  
Consistency Theory ◽  
Motivational Aspect ◽  
Human Need ◽  
The 1950S ◽  
Epistemic Aspect

From the 1950s onward, psychologists have generally assumed that people possess a general need for cognitive consistency whose frustration by an inconsistency elicits negative affect. We offer a novel perspective on this issue by introducing the distinction between epistemic and motivational impact of consistent and inconsistent cognitions. The epistemic aspect is represented by the updated expectancy of the outcome addressed in such cognitions. The motivational aspect stems from value (desirability) of that outcome. We show that neither the outcome’s value nor its updated expectancy are systematically related to cognitive consistency or inconsistency. Consequently, we question consistency’s role in the driving of affective responses, and the related presumption of a universal human need for cognitive consistency.

Multi-sources information fusion analysis of water inrush disaster in tunnels based on improved theory of evidence

2021 ◽  
Vol 113 ◽  
pp. 103948
Author(s):  
Shucai Li ◽  
Cong Liu ◽  
Zongqing Zhou ◽  
Liping Li ◽  
Shaoshuai Shi ◽  
...  
Keyword(s):  
Information Fusion ◽  
Water Inrush ◽  
Fusion Analysis ◽  
Theory Of Evidence

scholarly journals A MODIFIED D NUMBERS METHODOLOGY FOR ENVIRONMENTAL IMPACT ASSESSMENT

2017 ◽  
Vol 24 (2) ◽  
pp. 653-669 ◽  
Author(s):  
Ningkui WANG ◽  
Daijun WEI
Keyword(s):  
Environmental Impact ◽  
Impact Assessment ◽  
Environmental Impact Assessment ◽  
Previous Method ◽  
Combination Process ◽  
Dempster Shafer Theory ◽  
Shafer Theory ◽  
Theory Of Evidence ◽  
D Numbers ◽  
Commutative Property

Environmental impact assessment (EIA) is usually evaluated by many factors influenced by various kinds of uncertainty or fuzziness. As a result, the key issues of EIA problem are to rep­resent and deal with the uncertain or fuzzy information. D numbers theory, as the extension of Dempster-Shafer theory of evidence, is a desirable tool that can express uncertainty and fuzziness, both complete and incomplete, quantitative or qualitative. However, some shortcomings do exist in D numbers combination process, the commutative property is not well considered when multiple D numbers are combined. Though some attempts have made to solve this problem, the previous method is not appropriate and convenience as more information about the given evaluations rep­resented by D numbers are needed. In this paper, a data-driven D numbers combination rule is proposed, commutative property is well considered in the proposed method. In the combination process, there does not require any new information except the original D numbers. An illustrative example is provided to demonstrate the effectiveness of the method.

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