Quantitative Predictions in Quantum Decision Theory

IEEE Transactions on Systems Man and Cybernetics Systems , Vol. 48, Issue 3 pp. 366-381, 2018

17 Pages Posted: 18 Feb 2018 Last revised: 14 Jul 2018

See all articles by Vyacheslav I. Yukalov

Vyacheslav I. Yukalov

Joint Institute for Nuclear Research; D-MTEC, ETH Zurich

Didier Sornette

Risks-X, Southern University of Science and Technology (SUSTech); Swiss Finance Institute; ETH Zürich - Department of Management, Technology, and Economics (D-MTEC); Tokyo Institute of Technology

Date Written: August 15, 2016

Abstract

Quantum Decision Theory, advanced earlier by the authors, and illustrated for lotteries with gains, is generalized to the games containing lotteries with gains as well as losses. The mathematical structure of the approach is based on the theory of quantum measurements, which makes this approach relevant both for the description of decision making of humans and the creation of artificial quantum intelligence. General rules are formulated allowing for the explicit calculation of quantum probabilities representing the fraction of decision makers preferring the considered prospects. This provides a method to quantitatively predict decision-maker choices, including the cases of games with high uncertainty for which the classical expected utility theory fails. The approach is applied to experimental results obtained on a set of lottery gambles with gains and losses. Our predictions, involving no fitting parameters, are in very good agreement with experimental data. The use of quantum decision making in game theory is described. A principal scheme of creating quantum artificial intelligence is suggested.

Suggested Citation

Yukalov, Vyacheslav I. and Sornette, Didier, Quantitative Predictions in Quantum Decision Theory (August 15, 2016). IEEE Transactions on Systems Man and Cybernetics Systems , Vol. 48, Issue 3 pp. 366-381, 2018, Available at SSRN: https://ssrn.com/abstract=3125725

Vyacheslav I. Yukalov (Contact Author)

Joint Institute for Nuclear Research ( email )

Bogolubov Laboratory of Theoretical Physics
Dubna, 141980
Russia

D-MTEC, ETH Zurich ( email )

Zurich
Switzerland

Didier Sornette

Risks-X, Southern University of Science and Technology (SUSTech) ( email )

1088 Xueyuan Avenue
Shenzhen, Guangdong 518055
China

Swiss Finance Institute ( email )

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

ETH Zürich - Department of Management, Technology, and Economics (D-MTEC) ( email )

Scheuchzerstrasse 7
Zurich, ZURICH CH-8092
Switzerland
41446328917 (Phone)
41446321914 (Fax)

HOME PAGE: http://www.er.ethz.ch/

Tokyo Institute of Technology ( email )

2-12-1 O-okayama, Meguro-ku
Tokyo 152-8550, 52-8552
Japan

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