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Contributions to a computational theory of policy advice and avoidability*



We present the starting elements of a mathematical theory of policy advice and avoidability. More specifically, we formalize a cluster of notions related to policy advice, such as policy, viability, reachability, and propose a novel approach for assisting decision making, based on the concept of avoidability. We formalize avoidability as a relation between current and future states, investigate under which conditions this relation is decidable and propose a generic procedure for assessing avoidability. The formalization is constructive and makes extensive use of the correspondence between dependent types and logical propositions, decidable judgments are obtained through computations. Thus, we aim for a computational theory, and emphasize the role that computer science can play in global system science.



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This work was partially supported by the projects GRACeFUL (Grant agreement no. 640954) and CoeGSS (Grant agreement no. 676547), which have received funding from the European Union's Horizon 2020 research and innovation programme.



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Journal of Functional Programming
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Contributions to a computational theory of policy advice and avoidability*

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