Abstract
Policy exploration for downtown revitalization is becoming important in Japan. This chapter deals with a modeling and simulation project of downtown visitors’ shop-around behavior using an intelligent agent approach, by mainly devising and implementing the planning (dynamic scheduling/rescheduling), learning, and adaptation functions. In this chapter, we first explain the architecture of the agent simulation of shop-around behavior (ASSA) model. Each agent makes and remakes his or her schedule to visit shops based on time constraints and shop preferences, chooses alternative visits when he or she fails in an errand, and makes impulse stops at shops and detour actions. ASSAver.3 was reported based on detailed observations and surveys taken at the Asunal Kanayama shopping mall and in the Osu shopping district, Nagoya. Then we show a framework of evaluation that included redundancy indicators for shop visits and walk lengths, and similarity analysis of shop-visit sequences. Valid-check results were shown in the simulation performances of the two cases from these three aspects.
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Yoshida, T., Kaneda, T. (2013). The ASSA Project: An Intelligent Agent Simulation of Shop-Around Behavior. In: Murata, T., Terano, T., Takahashi, S. (eds) Agent-Based Approaches in Economic and Social Complex Systems VII. Agent-Based Social Systems, vol 10. Springer, Tokyo. https://doi.org/10.1007/978-4-431-54279-7_14
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DOI: https://doi.org/10.1007/978-4-431-54279-7_14
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