Artificial Collusion: Examining Supracompetitive Pricing by Q-Learning Algorithms

Arnoud den Boer, Janusz Meylahn, Maarten Pieter Schinkel

Research output: Working paper

17 Downloads (Pure)


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.
Original languageEnglish
PublisherSocial Science Research Network (SSRN)
Number of pages49
Publication statusPublished - 12 Dec 2022

Publication series

NameAmsterdam Law School Research Paper
PublisherAmsterdam Law School
NameAmsterdam Center for Law & Economics Working Paper
PublisherAmsterdam Center for Law & Economics


  • Collusion
  • Q-learning
  • Algorithm
  • Pricing


Dive into the research topics of 'Artificial Collusion: Examining Supracompetitive Pricing by Q-Learning Algorithms'. Together they form a unique fingerprint.

Cite this