IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2310.07867.html
   My bibliography  Save this paper

Cheap Talking Algorithms

Author

Listed:
  • Daniele Condorelli
  • Massimiliano Furlan

Abstract

We simulate behaviour of independent reinforcement learning algorithms playing the Crawford and Sobel (1982) game of strategic information transmission. We show that a sender and a receiver training together converge to strategies approximating the ex-ante optimal equilibrium of the game. Communication occurs to the largest extent predicted by Nash equilibrium. The conclusion is robust to alternative specifications of the learning hyperparameters and of the game. We discuss implications for theories of equilibrium selection in information transmission games, for work on emerging communication among algorithms in computer science, and for the economics of collusions in markets populated by artificially intelligent agents.

Suggested Citation

  • Daniele Condorelli & Massimiliano Furlan, 2023. "Cheap Talking Algorithms," Papers 2310.07867, arXiv.org, revised Dec 2023.
  • Handle: RePEc:arx:papers:2310.07867
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2310.07867
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Juan Ortner & Sylvain Chassang, 2018. "Making Corruption Harder: Asymmetric Information, Collusion, and Crime," Journal of Political Economy, University of Chicago Press, vol. 126(5), pages 2108-2133.
    2. Blume Andreas & Kim Yong-Gwan & Sobel Joel, 1993. "Evolutionary Stability in Games of Communication," Games and Economic Behavior, Elsevier, vol. 5(4), pages 547-575, October.
    3. Justin Pappas Johnson & Andrew Rhodes & Matthijs Wildenbeest, 2023. "Platform design when sellers use pricing algorithms," Post-Print hal-04226232, HAL.
    4. Borgers, Tilman & Sarin, Rajiv, 1997. "Learning Through Reinforcement and Replicator Dynamics," Journal of Economic Theory, Elsevier, vol. 77(1), pages 1-14, November.
    5. Emilio Calvano & Giacomo Calzolari & Vincenzo Denicolò & Sergio Pastorello, 2020. "Artificial Intelligence, Algorithmic Pricing, and Collusion," American Economic Review, American Economic Association, vol. 110(10), pages 3267-3297, October.
    6. Ying Chen & Navin Kartik & Joel Sobel, 2008. "Selecting Cheap-Talk Equilibria," Econometrica, Econometric Society, vol. 76(1), pages 117-136, January.
    7. Martino Banchio & Andrzej Skrzypacz, 2022. "Artificial Intelligence and Auction Design," NBER Chapters, in: Economics of Artificial Intelligence, National Bureau of Economic Research, Inc.
    8. Marhsall, Robert C. & Marx, Leslie M., 2014. "The Economics of Collusion: Cartels and Bidding Rings," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262525941, December.
    9. Frug, Alexander, 2016. "A note on optimal cheap talk equilibria in a discrete state space," Games and Economic Behavior, Elsevier, vol. 99(C), pages 180-185.
    10. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-881, September.
    11. Che, Yeon-Koo & Condorelli, Daniele & Kim, Jinwoo, 2018. "Weak cartels and collusion-proof auctions," Journal of Economic Theory, Elsevier, vol. 178(C), pages 398-435.
    12. Bajari, Patrick & Yeo, Jungwon, 2009. "Auction design and tacit collusion in FCC spectrum auctions," Information Economics and Policy, Elsevier, vol. 21(2), pages 90-100, June.
    13. Radner, Roy, 1980. "Collusive behavior in noncooperative epsilon-equilibria of oligopolies with long but finite lives," Journal of Economic Theory, Elsevier, vol. 22(2), pages 136-154, April.
    14. Waltman, Ludo & Kaymak, Uzay, 2008. "Q-learning agents in a Cournot oligopoly model," Journal of Economic Dynamics and Control, Elsevier, vol. 32(10), pages 3275-3293, October.
    15. Justin P. Johnson & Andrew Rhodes & Matthijs Wildenbeest, 2023. "Platform Design When Sellers Use Pricing Algorithms," Econometrica, Econometric Society, vol. 91(5), pages 1841-1879, September.
    16. Crawford, Vincent P & Sobel, Joel, 1982. "Strategic Information Transmission," Econometrica, Econometric Society, vol. 50(6), pages 1431-1451, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Inkoo Cho & Noah Williams, 2024. "Collusive Outcomes Without Collusion," Papers 2403.07177, arXiv.org.
    2. DeJong, D.V. & Blume, A. & Neumann, G., 1998. "Learning in Sender-Receiver Games," Other publications TiSEM 4a8b4f46-f30b-4ad2-bb0c-1, Tilburg University, School of Economics and Management.
    3. de Groot Ruiz, Adrian & Offerman, Theo & Onderstal, Sander, 2015. "Equilibrium selection in experimental cheap talk games," Games and Economic Behavior, Elsevier, vol. 91(C), pages 14-25.
    4. Emilio Calvano & Giacomo Calzolari & Vincenzo Denicolò & Sergio Pastorello, 2019. "Algorithmic Pricing What Implications for Competition Policy?," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 55(1), pages 155-171, August.
    5. Martino Banchio & Giacomo Mantegazza, 2022. "Artificial Intelligence and Spontaneous Collusion," Papers 2202.05946, arXiv.org, revised Sep 2023.
    6. Adrian Groot Ruiz & Theo Offerman & Sander Onderstal, 2014. "For those about to talk we salute you: an experimental study of credible deviations and ACDC," Experimental Economics, Springer;Economic Science Association, vol. 17(2), pages 173-199, June.
    7. Jonathan Newton, 2018. "Evolutionary Game Theory: A Renaissance," Games, MDPI, vol. 9(2), pages 1-67, May.
    8. Martino Banchio & Andrzej Skrzypacz, 2022. "Artificial Intelligence and Auction Design," NBER Chapters, in: Economics of Artificial Intelligence, National Bureau of Economic Research, Inc.
    9. George R. Neumann & Nathan E. Savin, 2000. "Learning and Communication in Sender-Receiver Games: An Econometric Investigation," Econometric Society World Congress 2000 Contributed Papers 1852, Econometric Society.
    10. Chen, Ying, 2011. "Perturbed communication games with honest senders and naive receivers," Journal of Economic Theory, Elsevier, vol. 146(2), pages 401-424, March.
    11. Zhang Xu & Mingsheng Zhang & Wei Zhao, 2024. "Algorithmic Collusion and Price Discrimination: The Over-Usage of Data," Papers 2403.06150, arXiv.org.
    12. Ianni, A., 2002. "Reinforcement learning and the power law of practice: some analytical results," Discussion Paper Series In Economics And Econometrics 203, Economics Division, School of Social Sciences, University of Southampton.
    13. Ivan Balbuzanov, 2019. "Lies and consequences," International Journal of Game Theory, Springer;Game Theory Society, vol. 48(4), pages 1203-1240, December.
    14. Asseyer, Andreas, 2020. "Collusion and delegation under information control," Discussion Papers 2020/3, Free University Berlin, School of Business & Economics.
    15. Chirantan Ganguly & Indrajit Ray, 2023. "Simple Mediation in a Cheap-Talk Game," Games, MDPI, vol. 14(3), pages 1-14, June.
    16. Golosov, Mikhail & Skreta, Vasiliki & Tsyvinski, Aleh & Wilson, Andrea, 2014. "Dynamic strategic information transmission," Journal of Economic Theory, Elsevier, vol. 151(C), pages 304-341.
    17. Fernando Lozano & Jaime Lozano & Mario García, 2007. "An artificial economy based on reinforcement learning and agent based modeling," Documentos de Trabajo 3907, Universidad del Rosario.
    18. Förster, Manuel & Riedel, Frank, 2016. "Distorted Voronoi languages," Center for Mathematical Economics Working Papers 458, Center for Mathematical Economics, Bielefeld University.
    19. Jason McKenzie Alexander & Brian Skyrms & Sandy Zabell, 2012. "Inventing New Signals," Dynamic Games and Applications, Springer, vol. 2(1), pages 129-145, March.
    20. Cason, Timothy N. & Saijo, Tatsuyoshi & Yamato, Takehiko & Yokotani, Konomu, 2004. "Non-excludable public good experiments," Games and Economic Behavior, Elsevier, vol. 49(1), pages 81-102, October.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2310.07867. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.