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Quantifying Algorithmic Improvements over Time

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cris.lastimport.scopus2024-02-12T19:42:44Z
dc.abstract.enAssessing the progress made in AI and contributions to the state of the art is of major concern to the community. Recently, Frechette et al. [2016] advocated performing such analysis via the Shapley value, a concept from coalitional game theory. In this paper, we argue that while this general idea is sound, it unfairly penalizes older algorithms that advanced the state of the art when introduced, but were then outperformed by modern counterparts. Driven by this observation, we introduce the temporal Shapley value, a measure that addresses this problem while maintaining the desirable properties of the (classical) Shapley value. We use the temporal Shapley value to analyze the progress made in (i) the different versions of the Quicksort algorithm; (ii) the annual SAT competitions 2007–2014; (iii) an annual competition of Constraint Programming, namely the MiniZinc challenge 2014–2016. Our analysis reveals novel insights into the development made in these important areas of research over time.
dc.affiliationUniwersytet Warszawski
dc.conference.countrySzwecja
dc.conference.datefinish2018-07-19
dc.conference.datestart2018-07-13
dc.conference.placeStockholm
dc.conference.seriesInternational Joint Conference on Artificial Intelligence
dc.conference.seriesInternational Joint Conference on Artificial Intelligence
dc.conference.seriesshortcutIJCAI
dc.conference.shortcutIJCAI 2018
dc.conference.weblinkhttps://www.ijcai-18.org/
dc.contributor.authorFrechette, Alexandre
dc.contributor.authorRahwan, Talal
dc.contributor.authorHoos, Holger
dc.contributor.authorLeyton-Brown, Kevin
dc.contributor.authorKotthoff, Lars
dc.contributor.authorMichalak, Tomasz
dc.date.accessioned2024-01-25T18:43:40Z
dc.date.available2024-01-25T18:43:40Z
dc.date.issued2018
dc.description.financeNie dotyczy
dc.identifier.doi10.24963/IJCAI.2018/716
dc.identifier.urihttps://repozytorium.uw.edu.pl//handle/item/117673
dc.pbn.affiliationcomputer and information sciences
dc.rightsClosedAccess
dc.sciencecloudnosend
dc.titleQuantifying Algorithmic Improvements over Time
dc.typeJournalArticle
dspace.entity.typePublication