A new method to predict the interference effect in quantum-like Bayesian networks

Abstract

Recent researches on human decision-making behaviors reveal some interesting phenomenon which are difficult to be explained under the structure of classic probability theory. The quantum-like Bayesian networks, like many other quantum models, have been developed to solve this problem. Powerful as these models are to explain the experimental results, these models usually contain unknown quantum parameters. In quantum-like Bayesian networks, such parameters represent the interference between different decisions. In this paper, a heuristic method is proposed to measure the interference effect. The proposed model also has its connection with the original quantum-like Bayesian networks. The experimental data from several Prisoners dilemma games are used to test the proposed method. The testing results illustrate the efficiency of the proposed method.

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Acknowledgements

The work is partially supported by National Natural Science Foundation of China (Grant Nos. 61573290, 61973332, 61503237). The authors greatly appreciate the reviews’ suggestions and the editors encouragement.

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Correspondence to Yong Deng.

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Dai, J., Deng, Y. A new method to predict the interference effect in quantum-like Bayesian networks. Soft Comput 24, 10287–10294 (2020). https://doi.org/10.1007/s00500-020-04693-2

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Keywords

  • Bayesian networks
  • Quantum decision making
  • Prisoner’s dilemma game
  • Sure thing principle
  • Quantum probability