The Gaming of Firm Strategy in High-Tech Industry: Human Agents and Artificial Intelligence Agents Intermingled in a Simulation Model

  • Hao Lee
  • Hiroshi Deguchi
Part of the Agent-Based Social Systems book series (ABSS, volume 2)


In this study, a hybrid-gaming simulation model was used instead of a normal computer simulation model. In the hybrid-gaming simulation, autonomous AI agents and human players competed against each other in a high-tech industrial model. Firm agents (both AI agents and human players) determined the levels of R&D investment and production investment.

The efficiencies of AI agents were compared with those of their human counterparts and the varying strategies of both AI agents and human players were assessed and verified. It was found that the learning speed of human players was much faster than AI agents and that the AI agents were validated and competed successfully against the human players.

Long-term maximization agents playing against human players performed well, but short-term maximization agents failed. This confirmed the importance of agent tuning when playing a hybrid-gaming simulation.

In future work, we will formulate our current model in an extensive game form and analyze the model more thoroughly. By carrying out more hybrid-gaming simulations with a dynamic model, it will be possible to analyze the model and create a robust theoretical formula. We will also analyze the relation between economic theory and the real economy by using both gaming simulation and hybrid-gaming simulation.


Market Share Good Score Technological Level Action Rule Production Investment 
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  1. 1.
    Nelson RR, Winter S (1982) An evolutionary theory of economic change. Belknap Press of Harvard University Press, Cambridge, MAGoogle Scholar
  2. 2.
    Arthur WB (1989) Competing technologies, increasing returns, and lock-in by historical events. Economic Journal 99:116–131CrossRefGoogle Scholar
  3. Takagi H, Kijima K, Deguchi H (1995) People and society in the multimedia century (in Japanese). NikkagekirenGoogle Scholar
  4. Kijima K, Deguchi H (1997) Inquiry of system knowledge (in Japanese). NikkagekirenGoogle Scholar
  5. Deguchi H (2000) Economy as a complex system (in Japanese). NikkagekirenGoogle Scholar
  6. Lee H, Deguchi H (2000) Technological innovation of high-tech industry (in Japanese).Google Scholar
  7. Lee H, Deguchi H (2000) Technological innovation of high-tech industry—agent based simulation with double loop learning. KSS′2000 JAIST, pp 224–229Google Scholar
  8. Lee H, Deguchi H (2001) Technological innovation of high-tech industry—agent based simulation with double loop learning. 4th Pacific Rim International Workshop on Multi-Agents, PRIMA2001, Taipei, TaiwanGoogle Scholar

Copyright information

© Springer-Verlag Tokyo 2005

Authors and Affiliations

  • Hao Lee
    • 1
  • Hiroshi Deguchi
    • 2
  1. 1.Graduate School of EconomicsKyoto UniversityKyotoJapan
  2. 2.Interdisciplinary Graduate School of Science and EngineeringTokyo Institute of TechnologyKyotoJapan

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