Summary
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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Nelson RR, Winter S (1982) An evolutionary theory of economic change. Belknap Press of Harvard University Press, Cambridge, MA
Arthur WB (1989) Competing technologies, increasing returns, and lock-in by historical events. Economic Journal 99:116–131
Takagi H, Kijima K, Deguchi H (1995) People and society in the multimedia century (in Japanese). Nikkagekiren
Kijima K, Deguchi H (1997) Inquiry of system knowledge (in Japanese). Nikkagekiren
Deguchi H (2000) Economy as a complex system (in Japanese). Nikkagekiren
Lee H, Deguchi H (2000) Technological innovation of high-tech industry (in Japanese).
Lee H, Deguchi H (2000) Technological innovation of high-tech industry—agent based simulation with double loop learning. KSS′2000 JAIST, pp 224–229
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, Taiwan
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Tokyo
About this chapter
Cite this chapter
Lee, H., Deguchi, H. (2005). The Gaming of Firm Strategy in High-Tech Industry: Human Agents and Artificial Intelligence Agents Intermingled in a Simulation Model. In: Arai, K., Deguchi, H., Matsui, H. (eds) Agent-Based Modeling Meets Gaming Simulation. Agent-Based Social Systems, vol 2. Springer, Tokyo. https://doi.org/10.1007/4-431-29427-9_4
Download citation
DOI: https://doi.org/10.1007/4-431-29427-9_4
Published:
Publisher Name: Springer, Tokyo
Print ISBN: 978-4-431-29426-9
Online ISBN: 978-4-431-29427-6
eBook Packages: Humanities, Social Sciences and LawSocial Sciences (R0)