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SSRN Electronic Journal
Article . 2022 . Peer-reviewed
Data sources: Crossref
EconStor
Research . 2022
Data sources: EconStor
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Artificial Collusion: Examining Supracompetitive Pricing by Q-Learning Algorithms

Examining Supracompetitive Pricing by Q-Learning Algorithms
Authors: den Boer, Arnoud V.; Meylahn, Janusz M.; Schinkel, Maarten Pieter;

Artificial Collusion: Examining Supracompetitive Pricing by Q-Learning Algorithms

Abstract

We examine recent claims that a particular Q-learning algorithm used by competitors 'autonomously' and systematically learns to collude, resulting in supracompetitive prices and extra profits for the firms sustained by collusive equilibria. A detailed analysis of the inner workings of this algorithm reveals that there is no immediate reason for alarm. We set out what is needed to demonstrate the existence of a colluding price algorithm that does form a threat to competition.

Country
Netherlands
Related Organizations
Keywords

L13, algorithm, ddc:330, Collusion, K21, L44, collusion, Algorithm, C63, pricing, Q-learning, Pricing

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    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
24
Top 10%
Top 10%
Top 10%