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Accession Number:
AD1096493
Title:
Applications of Quantum Probability Theory to Strategic Decision Making
Descriptive Note:
Technical Report,30 Sep 2015,29 Sep 2019
Corporate Author:
TRUSTEES OF INDIANA UNIVERSITY BLOOMINGTON United States
Report Date:
2019-08-19
Pagination or Media Count:
13.0
Abstract:
The broad and long term goal of this research program is to provide a new foundation for constructing probabilistic-dynamic systems from principles based on quantum as opposed to classical probability theory. To be clear, we are not interested in physics, and neither do we claim the brain is a quantum computer. Our interest lies solely in the application of mathematical principles from quantum theory to cognitive and decision sciences. Our recent research demonstrates that quantum theory provides a viable new direction for organizing and accounting for paradoxical findings from decision research using a unified and principled theoretical framework e.g., Busemeyer and Bruza, 2012 Busemeyer and Wang, 2014 Khrennikov, 2010 Wang, Busemeyer, Atmanspacher, and Pothos, 2013. So far we have applied these principles to both traditional, one-stage decision problems studied by decision researchers as well as dynamic Markov decision problems used in computer science and engineering. The more specific goal of the proposed research was to extend our initial work by developing new applications of quantum probability applied to dynamic, strategic, multiple agent decision situations. Specifically 1 We Developed new Markov and quantum models for perspective taking by opposing agents in dynamic, strategic games, and derived theoretical predictions that discriminate between the competing two classes of models. 2 We experimentally tested the proposed quantum model of perspective taking using probability judgments and decisions for self versus opponents in traditional economic strategic games, and reported evidence for the quantum model. 3 We develop engineering applications of quantum models to the strategic decision task of multiple agents deciding to acquire multiple targets in an uncertain and dynamically changing environment.
Distribution Statement:
APPROVED FOR PUBLIC RELEASE