Dynamic Bayesian Network Inferencing for Nonhomogenous Complex Systems
Thursday 25 June 2020
DARE ARC Training Centre presents its second talk in the DARE seminar series 2020, featuring Distinguished Professor Kerrie Mengersen from the Queensland University of Technology.
Dynamic Bayesian networks (DBNs) provide a versatile method for predictive, whole-of-systems modelling to support decision makers in managing natural systems subject to anthropogenic disturbances. However, DBNs typically assume a homogeneous Markov chain which we show can limit the dynamics that can be modelled especially for complex ecosystems that are susceptible to regime change (i.e. change in state transition probabilities). Such regime changes can occur as a result of exogenous inputs and/or because of past system states; the latter is known as path dependence.
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