Information Processing by Networks of Quantum Decision Makers

TL;DR

This paper introduces a quantum decision network model for multiple interacting agents, predicting collective decision dynamics and consensus formation, with results aligning well with empirical data.

Contribution

It generalizes quantum decision theory to multi-agent, multi-step scenarios, modeling information exchange and collective decision-making in quantum networks.

Findings

Describes probabilistic behavior of decision makers at initial stages

Shows decrease in difference between prospect probabilities and utility factors

Predicts emergence of consensus after multiple information exchanges

Abstract

We suggest a model of a multi-agent society of decision makers taking decisions being based on two criteria, one is the utility of the prospects and the other is the attractiveness of the considered prospects. The model is the generalization of quantum decision theory, developed earlier for single decision makers realizing one-step decisions, in two principal aspects. First, several decision makers are considered simultaneously, who interact with each other through information exchange. Second, a multistep procedure is treated, when the agents exchange information many times. Several decision makers exchanging information and forming their judgement, using quantum rules, form a kind of a quantum information network, where collective decisions develop in time as a result of information exchange. In addition to characterizing collective decisions that arise in human societies, such networks can describe dynamical processes occurring in artificial quantum intelligence composed of several parts or in a cluster of quantum computers. The practical usage of the theory is illustrated on the dynamic disjunction effect for which three quantitative predictions are made: (i) the probabilistic behavior of decision makers at the initial stage of the process is described; (ii) the decrease of the difference between the initial prospect probabilities and the related utility factors is proved; (iii) the existence of a common consensus after multiple exchange of information is predicted. The predicted numerical values are in very good agreement with empirical data.