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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Identification Number : 10.1093/oxrep/grab011

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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