Assad, Stephanie, Calvano, Emilio, Calzolari, Giacomo, Clark, Robert, Denicolo, Vincenzo, Ershov, Daniel, Johnson, Justin Pappas, Pastorello, Sergio, Rhodes, Andrew, XU, Lei and Wildenbeest, Matthijs (2021) Autonomous algorithmic collusion: Economic research and policy implications. Oxford Review of Economic Policy, vol. 37 (n° 3). pp. 459-478.
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Abstract
Markets are being populated with new generations of pricing algorithms, powered with Artificial Intelligence, that have the ability to autonomously learn to operate. This ability can be both a source of efficiency and cause of concern for the risk that algorithms autonomously and tacitly learn to collude. In this paper we explore recent developments in the economic literature
and discuss implications for policy.
Item Type: | Article |
---|---|
Language: | English |
Date: | September 2021 |
Refereed: | Yes |
Place of Publication: | Oxford |
Uncontrolled Keywords: | Algorithmic Pricing, Antitrust, Competition Policy, Artificial Intelligence, Collusion, Platforms. |
Subjects: | B- ECONOMIE ET FINANCE |
Divisions: | TSE-R (Toulouse) |
Site: | UT1 |
Date Deposited: | 30 Sep 2021 14:06 |
Last Modified: | 05 Jan 2024 10:09 |
OAI Identifier: | oai:tse-fr.eu:125586 |
URI: | https://publications.ut-capitole.fr/id/eprint/43526 |
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Autonomous algorithmic collusion: economic research and policy implications. (deposited 27 May 2021 14:05)
- Autonomous algorithmic collusion: Economic research and policy implications. (deposited 30 Sep 2021 14:06) [Currently Displayed]