Location of Repository

Quantum-Like Bayesian Networks for Modeling Decision Making

By Catarina eMoreira and Andreas eWichert

Abstract

In this work, we explore an alternative quantum structure to perform quantum probabilistic inferences to accommodate the paradoxical findings of the Sure Thing Principle. We propose a Quantum-Like Bayesian Network, which consists in replacing classical probabilities by quantum probability amplitudes. However, since this approach suffers from the problem of exponential growth of quantum parameters, we also propose a similarity heuristic that automatically fits quantum parameters through vector similarities. This makes the proposed model general and predictive in contrast to the current state of the art models, which cannot be generalized for more complex decision scenarios and that only provide an explanatory nature for the observed paradoxes. In the end, the model that we propose consists in a nonparametric method for estimating inference effects from a statistical point of view. It is a statistical model that is simpler than the previous quantum dynamic and quantum-like models proposed in the literature. We tested the proposed network with several empirical data from the literature, mainly from the Prisoner's Dilemma game and the Two Stage Gambling game. The results obtained show that the proposed quantum Bayesian Network is a general method that can accommodate violations of the laws of classical probability theory and make accurate predictions regarding human decision-making in these scenarios

Topics: Decision Making, Quantum Cognition, bayesian networks, quantum probability theory, sure thing principle, Psychology, BF1-990
Publisher: Frontiers Media S.A.
Year: 2016
DOI identifier: 10.3389/fpsyg.2016.00011
OAI identifier: oai:doaj.org/article:c38a518cbec14fbdab667f09b9b7acb5
Journal:
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • https://doaj.org/toc/1664-1078 (external link)
  • http://journal.frontiersin.org... (external link)
  • https://doaj.org/article/c38a5... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.