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Algorithmic Collusion in Cournot Duopoly Market: Evidence from Experimental Economics

Nan Zhou, Li Zhang, Shijian Li, Zhijian Wang

arXiv 21 Feb 2018 · Econometrics · 3 citations (OpenAlex)

arXiv:1802.08061 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Algorithmic collusion is an emerging concept in current artificial intelligence age. Whether algorithmic collusion is a creditable threat remains as an argument. In this paper, we propose an algorithm which can extort its human rival to collude in a Cournot duopoly competing market. In experiments, we show that, the algorithm can successfully extorted its human rival and gets higher profit in long run, meanwhile the human rival will fully collude with the algorithm. As a result, the social welfare declines rapidly and stably. Both in theory and in experiment, our work confirms that, algorithmic collusion can be a creditable threat. In application, we hope, the frameworks, the algorithm design as well as the experiment environment illustrated in this work, can be an incubator or a test bed for researchers and policymakers to handle the emerging algorithmic collusion.

Citation extraction

33
references
69
in-text mentions
33
distinct cited
1
self-citations
8,008
main-text words

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Capobianco, A., Gonzaga, P. & Nyeso, A (2017) Algorithms and collusion - background note by the secretariat1.000104100%
2Friedman, D., Huck, S., Oprea, R. & Weidenholzer, S (2015) From imitation to collusion: Long-run learning in a low-information environment1.000103100%
3Tirole, J (1988) The theory of industrial organization0.92843100%
4Mcavoy, A. & Hauert, C (2016) Autocratic strategies for iterated games with arbitrary action spaces0.81142100%
5Press, W. H. & Dyson, F. J (2012) Iterated prisoners dilemma contains strategies that dominate any evolutionary opponent0.73732100%
6Varian, H (2018) Artificial intelligence, economics, and industrial organization0.73732100%
7Wang, Z., Zhou, Y., Lien, J. W., Zheng, J. & Xu, B (2016) Extortion can outperform generosity in the iterated prisoner's dilemma self0.73732100%
8Ballard, D. & Naik, A (2017) Algorithms, artificial intelligence, and joint conduct0.64422100%
9Cox, J. C. & Walker, M (1998) Learning to play cournot duopoly strategies0.64422100%
10Engel, C (2015) Tacit collusion: The neglected experimental evidence0.64422100%

Showing the top 10 of 33 scored citations.