Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
718987 | IFAC Proceedings Volumes | 2012 | 6 Pages |
Abstract
Policy making is a multi-step process involving several actors. It affects international stability due to the interdependency of the contemporary world. Policy making processes that are evidence-based, model-based or participatory can benefit from the use of support systems. We individuate causal beliefs as a critical notion for policy making and policy making support systems. Representation, modeling and discovery of causal beliefs can rely on a wide range of techniques developed in Artificial Intelligence, Machine Learning and Statistical Causal Inference. We argue that the inclusion of such techniques in policy making support system can contribute to solve some relevant issues related to policy making process.
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