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Learning competitive pricing strategies by multi-agent reinforcement learning

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  • Kutschinski, Erich
  • Uthmann, Thomas
  • Polani, Daniel

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  • Kutschinski, Erich & Uthmann, Thomas & Polani, Daniel, 2003. "Learning competitive pricing strategies by multi-agent reinforcement learning," Journal of Economic Dynamics and Control, Elsevier, vol. 27(11-12), pages 2207-2218, September.
  • Handle: RePEc:eee:dyncon:v:27:y:2003:i:11-12:p:2207-2218
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    References listed on IDEAS

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    1. Madhavan, Ananth, 2000. "Market microstructure: A survey," Journal of Financial Markets, Elsevier, vol. 3(3), pages 205-258, August.
    2. Varian, Hal R, 1980. "A Model of Sales," American Economic Review, American Economic Association, vol. 70(4), pages 651-659, September.
    3. Nicolaas J. Vriend, 1996. "A model of market-making," Economics Working Papers 184, Department of Economics and Business, Universitat Pompeu Fabra.
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    Cited by:

    1. Tharakunnel, Kurian & Bhattacharyya, Siddhartha, 2009. "Single-leader-multiple-follower games with boundedly rational agents," Journal of Economic Dynamics and Control, Elsevier, vol. 33(8), pages 1593-1603, August.
    2. Ахмадеев Б.А.* & Макаров В.Л.**, 2019. "Система Оценки Проектов На Основе Комбинированных Методов Компьютерной Оптимизации," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 55(2), pages 5-23, апрель.
    3. Tong Zhang & B. Brorsen, 2011. "Oligopoly firms with quantity-price strategic decisions," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 6(2), pages 157-170, November.
    4. Junyi Xu, 2021. "Reinforcement Learning in a Cournot Oligopoly Model," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1001-1024, December.
    5. Alexander Kastius & Rainer Schlosser, 2022. "Dynamic pricing under competition using reinforcement learning," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(1), pages 50-63, February.
    6. Zhang, Tong & Brorsen, B. Wade, 2008. "Price Competition with Particle Swarm Optimization: An Agent-Based Artificial Model," 2008 Annual Meeting, February 2-6, 2008, Dallas, Texas 6780, Southern Agricultural Economics Association.
    7. Viehmann, Johannes & Lorenczik, Stefan & Malischek, Raimund, 2021. "Multi-unit multiple bid auctions in balancing markets: An agent-based Q-learning approach," Energy Economics, Elsevier, vol. 93(C).
    8. Ruben Geer & Arnoud V. Boer & Christopher Bayliss & Christine S. M. Currie & Andria Ellina & Malte Esders & Alwin Haensel & Xiao Lei & Kyle D. S. Maclean & Antonio Martinez-Sykora & Asbjørn Nilsen Ris, 2019. "Dynamic pricing and learning with competition: insights from the dynamic pricing challenge at the 2017 INFORMS RM & pricing conference," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 18(3), pages 185-203, June.
    9. Torsten J. Gerpott & Jan Berends, 2022. "Competitive pricing on online markets: a literature review," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(6), pages 596-622, December.
    10. Duffy, John, 2006. "Agent-Based Models and Human Subject Experiments," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 19, pages 949-1011, Elsevier.
    11. Tong Zhang & B. Brorsen, 2009. "Particle Swarm Optimization Algorithm for Agent-Based Artificial Markets," Computational Economics, Springer;Society for Computational Economics, vol. 34(4), pages 399-417, November.
    12. Azadeh, A. & Skandari, M.R. & Maleki-Shoja, B., 2010. "An integrated ant colony optimization approach to compare strategies of clearing market in electricity markets: Agent-based simulation," Energy Policy, Elsevier, vol. 38(10), pages 6307-6319, October.
    13. Leonardo Bargigli & Gabriele Tedeschi, 2013. "Major trends in agent-based economics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(2), pages 211-217, October.
    14. Marco Raberto & Andrea Teglio & Silvano Cincotti, 2008. "Integrating Real and Financial Markets in an Agent-Based Economic Model: An Application to Monetary Policy Design," Computational Economics, Springer;Society for Computational Economics, vol. 32(1), pages 147-162, September.
    15. Ruben van de Geer & Arnoud V. den Boer & Christopher Bayliss & Christine Currie & Andria Ellina & Malte Esders & Alwin Haensel & Xiao Lei & Kyle D. S. Maclean & Antonio Martinez-Sykora & Asbj{o}rn Nil, 2018. "Dynamic Pricing and Learning with Competition: Insights from the Dynamic Pricing Challenge at the 2017 INFORMS RM & Pricing Conference," Papers 1804.03219, arXiv.org.
    16. Viehmann, Johannes & Lorenczik, Stefan & Malischek, Raimund, 2018. "Multi-unit multiple bid auctions in balancing markets: an agent-based Q-learning approach," EWI Working Papers 2018-3, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    17. Moreno-Izquierdo, Luis & Egorova, Galina & Peretó-Rovira, Alexandre & Más-Ferrando , Adrián, 2018. "Exploring the use of artificial intelligence in price maximisation in the tourism sector: its application in the case of Airbnb in the Valencian Community," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 42, pages 113-128.
    18. Callum Rhys Tilbury, 2022. "Reinforcement Learning for Economic Policy: A New Frontier?," Papers 2206.08781, arXiv.org, revised Feb 2023.

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