On Understanding Diffusion Dynamics of Patrons at a Theme Park
AAMAS '14: Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems: May 5-9, 2014, Paris, Page: 1501-1502
2014
- 231Usage
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Metrics Details
- Usage231
- Downloads162
- Abstract Views69
Conference Paper Description
In this work, we focus on the novel application of learning the diffusion dynamics of visitors among attractions at a large theme park using only aggregate information about waiting times at attractions. Main contributions include formulating optimisation models to compute diffusion dynamics. We also developed algorithm capable of dealing with noise in the data to populate parameters in the optimization model. We validated our approach using cross validation on a real theme park data set. Our approach provides an accuracy of about 80$% for popular attractions, providing solid empirical support for our diffusion models.
Bibliographic Details
International Foundation for Autonomous Agents and Multiagent Systems
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