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QuLBIT: Quantum-Like Bayesian Inference Technologies for Cognition and Decision

Authors :
Moreira, Catarina
Hammes, Matheus
Kurdoglu, Rasim Serdar
Bruza, Peter
Source :
Proceedings of the 42nd Annual Meeting of the Cognitive Science Society, 2020
Publication Year :
2020

Abstract

This paper provides the foundations of a unified cognitive decision-making framework (QulBIT) which is derived from quantum theory. The main advantage of this framework is that it can cater for paradoxical and irrational human decision making. Although quantum approaches for cognition have demonstrated advantages over classical probabilistic approaches and bounded rationality models, they still lack explanatory power. To address this, we introduce a novel explanatory analysis of the decision-maker's belief space. This is achieved by exploiting quantum interference effects as a way of both quantifying and explaining the decision-maker's uncertainty. We detail the main modules of the unified framework, the explanatory analysis method, and illustrate their application in situations violating the Sure Thing Principle.

Details

Database :
arXiv
Journal :
Proceedings of the 42nd Annual Meeting of the Cognitive Science Society, 2020
Publication Type :
Report
Accession number :
edsarx.2006.02256
Document Type :
Working Paper