{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T20:57:19Z","timestamp":1776891439227,"version":"3.51.2"},"reference-count":44,"publisher":"Centre pour la Communication Scientifique Directe (CCSD)","license":[{"start":{"date-parts":[[2017,10,24]],"date-time":"2017-10-24T00:00:00Z","timestamp":1508803200000},"content-version":"unspecified","delay-in-days":296,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Funct. Prog."],"published-print":{"date-parts":[[2017]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    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\n                    <jats:italic>policy<\/jats:italic>\n                    ,\n                    <jats:italic>viability<\/jats:italic>\n                    ,\n                    <jats:italic>reachability<\/jats:italic>\n                    , and propose a novel approach for assisting decision making, based on the concept of\n                    <jats:italic>avoidability<\/jats:italic>\n                    . 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\n                    <jats:italic>computational<\/jats:italic>\n                    theory, and emphasize the role that computer science can play in global system science.\n                  <\/jats:p>","DOI":"10.1017\/s0956796817000156","type":"journal-article","created":{"date-parts":[[2017,10,24]],"date-time":"2017-10-24T00:27:36Z","timestamp":1508804856000},"source":"Crossref","is-referenced-by-count":7,"title":["Contributions to a computational theory of policy advice and avoidability"],"prefix":"10.46298","volume":"27","author":[{"given":"NICOLA","family":"BOTTA","sequence":"first","affiliation":[]},{"given":"PATRIK","family":"JANSSON","sequence":"additional","affiliation":[]},{"given":"CEZAR","family":"IONESCU","sequence":"additional","affiliation":[]}],"member":"25203","published-online":{"date-parts":[[2017,10,24]]},"reference":[{"key":"S0956796817000156_ref43","volume-title":"The Curious Role of \u201cLearning\u201d in Climate Policy: Should We Wait for More Data?","author":"Webster","year":"2000"},{"key":"S0956796817000156_ref12","unstructured":"CoeGSS. 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