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Reinforcement Learning For Decision-Making In A Business Simulator

Author

Listed:
  • JAVIER GARCÍA

    (Computer Science Department, Universidad Carlos III de Madrid, Avenida de la Universidad 30, 28911 Leganés, Madrid, Spain)

  • FERNANDO BORRAJO

    (Faculty of Economics and Business Administration, Universidad Autónoma de Madrid, Ctra. de Colmenar Viejo, Km 15, 28049 Madrid, Spain)

  • FERNANDO FERNÁNDEZ

    (Computer Science Department, Universidad Carlos III de Madrid, Avenida de la Universidad 30, 28911 Leganés, Madrid, Spain)

Abstract

Business simulators are powerful tools for both supporting the decision-making process of business managers as well as for business education. An example is SIMBA (SIMulator for Business Administration), a powerful simulator which is currently used as a web-based platform for business education in different institutions. In this paper, we propose the application of reinforcement learning (RL) for the creation of intelligent agents that can manage virtual companies in SIMBA. This application is not trivial, given the particular intrinsic characteristics of SIMBA: it is a generalized domain where hundreds of parameters modify the domain behavior; it is a multi-agent domain where both cooperation and competition among different agents can coexist; it is required to set dozens of continuous decision variables for a given business decision, which is made only after the study of hundreds of continuous variables. We will demonstrate empirically that all these challenges can be overcome through the use of RL, showing results for different learning scenarios.

Suggested Citation

  • Javier García & Fernando Borrajo & Fernando Fernández, 2012. "Reinforcement Learning For Decision-Making In A Business Simulator," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 11(05), pages 935-960.
    • Handle: RePEc:wsi:ijitdm:v:11:y:2012:i:05:n:s0219622012500277
    DOI: 10.1142/S0219622012500277
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    References listed on IDEAS

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    1. David F. Midgley & Robert E. Marks & Lee C. Cooper, 1997. "Breeding Competitive Strategies," Management Science, INFORMS, vol. 43(3), pages 257-275, March.
    2. Martin J. Osborne & Ariel Rubinstein, 1994. "A Course in Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262650401, December.
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    Cited by:

    1. Johanna Bragge & Henrik Kallio & Tomi Seppälä & Timo Lainema & Pekka Malo, 2017. "Decision-Making in a Real-Time Business Simulation Game: Cultural and Demographic Aspects in Small Group Dynamics," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(03), pages 779-815, May.

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