Differentiable Economics: Strategic Behavior, Mechanisms, and Machine Learning.
Differentiable economics applies neural networks and machine learning to reformulate economic models as differentiable structures, allowing the use of gradient-based optimization. This framework addresses the difficulty of finding Bayes–Nash equilibria in auctions and market games by combining reinf...
| Publicado en: | Communications of the ACM Vol. 68; no. 9; pp. 80 - 89 |
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| Autores principales: | , |
| Formato: | Artículo |
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Association for Computing Machinery
Sep2025
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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=187620990&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 187620990 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00010782 ACM jtl: Communications of the ACM issn: 00010782 maglogo: N pubinfo: dt: Sep2025 vid: 68 iid: 9 pid: 68 pub: Association for Computing Machinery artinfo: ui: 187620990 10.1145/3725809 ppf: 80 ppct: 9 formats: tig: atl: Differentiable Economics: Strategic Behavior, Mechanisms, and Machine Learning. aug: au: Bichler, Martin Parkes, David C. affil: Technical University of Munich, Munchen, Bavaria, Germany Harvard University, Boston, Massachusetts, United States su: Differentiable functions Economic models Machine learning Artificial neural networks Optimization algorithms Game theory sug: subj: Differentiable functions Economic models Machine learning Artificial neural networks Optimization algorithms Game theory ab: Differentiable economics applies neural networks and machine learning to reformulate economic models as differentiable structures, allowing the use of gradient-based optimization. This framework addresses the difficulty of finding Bayes–Nash equilibria in auctions and market games by combining reinforcement learning with self-play, thus overcoming traditional computational obstacles in game theory. Beyond equilibrium analysis, the approach also enables automated mechanism design, yielding revenue-maximizing auctions and other solutions that are inaccessible through purely analytical methods. pubtype: Periodical doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2025 holdings: @attributes: islocal: N |
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