Computer Science > Computer Science and Game Theory
arXiv:2407.03521 (cs)
[Submitted on 3 Jul 2024 (v1), last revised 19 Mar 2025 (this version, v3)]
Title:Algorithmic Collusion And The Minimum Price Markov Game
View a PDF of the paper titled Algorithmic Collusion And The Minimum Price Markov Game, by Igor Sadoune and 2 other authors
View PDFHTML (experimental)Abstract:This paper introduces the Minimum Price Markov Game (MPMG), a theoretical model that reasonably approximates real-world first-price markets following the minimum price rule, such as public auctions. The goal is to provide researchers and practitioners with a framework to study market fairness and regulation in both digitized and non-digitized public procurement processes, amid growing concerns about algorithmic collusion in online markets. Using multi-agent reinforcement learning-driven artificial agents, we demonstrate that (i) the MPMG is a reliable model for first-price market dynamics, (ii) the minimum price rule is generally resilient to non-engineered tacit coordination among rational actors, and (iii) when tacit coordination occurs, it relies heavily on self-reinforcing trends. These findings contribute to the ongoing debate about algorithmic pricing and its implications.
| Subjects: | Computer Science and Game Theory (cs.GT); General Economics (econ.GN) |
| Cite as: | arXiv:2407.03521 [cs.GT] |
| (orarXiv:2407.03521v3 [cs.GT] for this version) | |
| https://doi.org/10.48550/arXiv.2407.03521 arXiv-issued DOI via DataCite |
Submission history
From: Igor Sadoune [view email][v1] Wed, 3 Jul 2024 21:40:34 UTC (1,261 KB)
[v2] Tue, 12 Nov 2024 14:46:52 UTC (5,646 KB)
[v3] Wed, 19 Mar 2025 16:19:22 UTC (5,601 KB)
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View a PDF of the paper titled Algorithmic Collusion And The Minimum Price Markov Game, by Igor Sadoune and 2 other authors
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