Quantum Bayesian Decision-Making

نویسندگان

چکیده

As a compact representation of joint probability distributions over dependence graph random variables, and tool for modelling reasoning in the presence uncertainty, Bayesian networks are great importance artificial intelligence to combine domain knowledge, capture causal relationships, or learn from incomplete datasets. Known as NP-hard problem classical setting, inference pops up class algorithms worth explore quantum framework. This paper explores such research direction improves on previous proposals by judicious use utility function an entangled configuration. It proposes completely mechanical decision-making process with proven computational advantage. A prototype implementation Qiskit (a Python-based program development kit IBM Q machine) is discussed proof-of-concept.

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ژورنال

عنوان ژورنال: Foundations of Science

سال: 2021

ISSN: ['1572-8471', '1233-1821']

DOI: https://doi.org/10.1007/s10699-021-09781-6