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arXiv:1508.06973

The Relation Between Acausality and Interference in Quantum-Like Bayesian Networks

Catarina Moreira, Andreas Wichert

Published Aug 26, 2015• 1 citation
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Abstract

We analyse a quantum-like Bayesian Network that puts together cause/effect relationships and semantic similarities between events. These semantic similarities constitute acausal connections according to the Synchronicity principle and provide new relationships to quantum like probabilistic graphical models. As a consequence, beliefs (or any other event) can be represented in vector spaces, in which quantum parameters are determined by the similarities that these vectors share between them. Events attached by a semantic meaning do not need to have an explanation in terms of cause and effect.

DOI
10.48550/arxiv.1508.06973

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