Quantum-like Uncertainty Quantification (QUQ) for urban sustainability and resilience

Urban sustainability requires holistically the inclusion of energy systems, human systems, urban systems and environmental systems. Novel frameworks are necessary to model, understand and predict the dynamic responses of complex engineering systems under uncertainty. Empirical findings show that humans tend to violate the expected utility theory and consequently the laws of classical probability: models beyond Bayesian approaches are needed. It is here explored the Quantum-like probability (QP) grounded on non-Kolmogorovian probabilities including entanglement in addition to the correlations. Modern cognitive psychology argues that QP can describe human decisions in an elegant framework. The Quantum-like Bayesian Networks (QBN) substitute the Bayes’ calculus with the quantum amplification wave function. Moreover, QBN can solve several problem which are considered unsolvable for classical Bayesian Networks (BN): (i) presence of deep uncertainty, e.g. no evidence observed (while QBN and BN coincide in presence of low levels of uncertainty), (ii) non-commutative systems, where the order of the priors may affect the posteriors, (iii) intransitive systems, dominantly circular, with interaction, sinchronicity and co-evolution of multiple agents, (iv) systems with complex feedback loops, (v) chaotic and complex systems where emergent properties can arise, (vi) cases of hidden interdependencies where the input variables can be dependent even if they are not linked and/or not share a common parent node. In this paper we introduce a framework of Quantum-like Uncertainty Quantification and Risk Analysis (QUQ). Moreover, for the first time it is discussed the potential of QBN for sustainability and resilience of urban communities modelled as Socio-Ecological-Technical systems under uncertainty.