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MJ Barons, X Zhong and JQ Smith

Dynamic Bayesian Networks for decision support and sugar food security

Abstract: Food security, access to sufficient safe, nutritious food for active and healthy lives, is enormously important for individuals and a key responsibility of national and international governments. Food security is determined by a huge range of factors over many scales ranging from global climate and water to individuals' food choices and waste behaviours. Food security policy decision-makers need to take account of these factors and their interdependencies using available data and experts judgements. Dynamic Bayesian networks are powerful models that are able to capture the dependencies between variables and combine data with expert opinion in a rigorous fashion as they develop over time. They have been shown to be appropriate for various types of decision support; however their application to food security policy is novel. Here we design a Dynamic Bayesian network approach to provide decision support for food security as associated with potential instabilities within the sugar industry.