Int J Performability Eng ›› 2020, Vol. 16 ›› Issue (10): 1556-1565.doi: 10.23940/ijpe.20.10.p7.15561565

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Probabilistic Dynamic Decision Making based on Bimodal Implicit Information Quantum Model

Hui Lia,b,*   

  1. aSchool of Computer and Information Engineering, Harbin University of Commerce, Harbin, 150028, China;
    bHeilongjiang Provincial Key Laboratory of Electronic Commerce and Information Processing, Harbin, 150028, China
  • Submitted on ; Revised on ; Accepted on
  • Contact: * E-mail address:
  • About author:Hui Li is an associate professor of the School of Computer & Information Engineering at Harbin University of Commerce. His research interests include intelligent control and decision making and quantum information processing.

Abstract: To address the dynamic decision making problem, in this paper, we propose a probabilistic decision method based on bimodal implicit information quantum model. By means of constructing the quantum dynamic decision making system, we analyze the superposition nature of states and describe the time-varying evolution and state projection response. Secondly, on account of the bounded rationality hypothesis, the negatively related Hamilton operator is designed. After introducing subjective implicit information of decision-makers as the characteristic index of projection operator, we revise the state response matrixes. Then, the implicit information quantum weighted model is established for a bimodal decision system. Finally, according to synthesizing time-varying evolution and wave packet projection collapsing, an example analysis is given to illustrate the effectiveness of the proposed approach in categorization decision making application.

Key words: quantum model, probabilistic dynamic decision-making, bimodal implicit information, state projection