Why Simpler Computer Simulation Models Can Be Epistemically Better for Informing Decisions.
For computer simulation models to usefully inform climate risk management, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many times over, and because computing resources are finite, uncertainty assessment is more feasible using mod...
| Publicado en: | Philosophy of Science Vol. 88; no. 2; pp. 213 - 234 |
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| Autores principales: | , , , |
| Formato: | Artículo |
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Cambridge University Press
Apr2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=149691987&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 149691987 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00318248 PSC jtl: Philosophy of Science issn: 00318248 maglogo: N pubinfo: dt: Apr2021 vid: 88 iid: 2 pid: 15979 pub: Cambridge University Press artinfo: ui: 149691987 10.1086/711501 ppf: 213 ppct: 21 formats: fmt: @attributes: type: P size: 530KB tig: atl: Why Simpler Computer Simulation Models Can Be Epistemically Better for Informing Decisions. aug: au: Helgeson, Casey Srikrishnan, Vivek Keller, Klaus Tuana, Nancy su: Computer simulation Philosophy of science Philosophical literature Simulation methods & models Science in literature sug: subj: Computer simulation Philosophy of science Philosophical literature Simulation methods & models Science in literature ab: For computer simulation models to usefully inform climate risk management, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many times over, and because computing resources are finite, uncertainty assessment is more feasible using models that demand less computer processor time. Such models are generally simpler in the sense of being more idealized, or less realistic. So modelers face a trade-off between realism and uncertainty quantification. Seeing this trade-off for the important epistemic issue that it is requires a shift in perspective from the established simplicity literature in philosophy of science. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Copyright of Philosophy of Science is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. item: Philosophy of Science holder: Cambridge University Press dt: @attributes: year: 2021 holdings: @attributes: islocal: N |
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