Abstract
Because of the dynamic and heterogeneous interactions among human beings with their bounded rationality, a service system discussed in Service Science, Management, and Engineering (SSME) is recognized as a complex adaptive system to which quantitative scientific analysis is difficult to apply. In this chapter, we introduce 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. Recently, agent-based social simulations are utilized to support the decision-making of city planners for various real social issues. For this purpose, we have developed a large-scale social simulation framework “X10-based Agent Simulation on Distributed Infrastructure (XASDI).” In this chapter, we will introduce our earlier work with a small number of agents and then describe the large-scale social simulation framework and its applications.
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Acknowledgements
The work with XASDI framework and its applications was supported by CREST, JST.
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Mizuta, H. (2022). Agent-Based Simulation for Service and Social Systems and Large-Scale Social Simulation Framework. In: Aruka, Y. (eds) Digital Designs for Money, Markets, and Social Dilemmas. Evolutionary Economics and Social Complexity Science, vol 28. Springer, Singapore. https://doi.org/10.1007/978-981-19-0937-5_7
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DOI: https://doi.org/10.1007/978-981-19-0937-5_7
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