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The Synchronicity Principle Under Quantum Probabilistic Inferences
journal contributionposted on 15.10.2019, 10:56 by Catarina Moreira, Andreas Wichert
We propose a new quantum Bayesian Network model in order to compute probabilistic inferÂ¬ences in decision making scenarios. The application of a quantum paradigm to decision making generates interference effects that influence probabilistic inferences. These effects do not exist in a classical setting and constitute a major issue in the decision process, because they generate quantum parameters that highly increase with the amount of uncertainty of the problem. To automatically compute these quantum parameters, we propose a heuristic inspired by Jungâ€™s Synchronicity principle. Synchronicity can be defined by a significant coincidence that appears beÂ¬tween a mental state and an event occurring in the external world. It is the occurrence of meaningful, but not causally connected events. We tested our quantum Bayesian Network together with the Synchronicity inspired heuristic in empirical experiments related to categorization/decision in which the law of total probability was being violated. Results showed that the proposed quantum model was able to simulate the observed empirical findings from the experiments. We then applied our model to a more general scenario and showed the differences between classical and quantum inferences in a Lung Cancer medical diagnosis Bayesian Network.