Agent-Based Simulation for Service Science

  • Hideyuki MizutaEmail author
Part of the Service Science: Research and Innovations in the Service Economy book series (SSRI)


The most important building blocks of service systems are human beings. Because of the dynamic and heterogeneous interactions among human beings with their bounded rationality, a service system is recognized as a complex adaptive system to which quantitative scientific analysis is difficult to apply. In this chapter, we discuss a computational approach for such complex adaptive systems called agent-based simulation. Since the 1990s, agent-based simulation has gained significance as a tool to reproduce complex stock market interactions by modeling human traders as software agents. Computer scientists and social scientists are working together to model social systems with interacting heterogeneous agents and simulating their dynamic behaviors using computers. As our computational resources continue to grow rapidly, the application areas for agent-based simulations are spreading into areas of social science that overlap with SSME research. We will introduce several examples of agent-based simulations for marketing, for emissions trading, for communications, and for traffic systems and discuss the contributions of this scientific approach to the study of service systems.


Complex Adaptive System Marginal Abatement Cost Online Auction Double Auction Traffic Simulator 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.IBM JapanTokyoJapan

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