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Conference Paper
Objectivity based Self-Evolving Agent Model Validation for Social Issue Simulation
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- Authors
- Joonyoung Jung, Jang Won Bae, Chunhee Lee, Dong-oh Kang, Euihyun Paik
- Issue Date
- 2018-10
- Citation
- International Conference on Information and Communication Technology Convergence (ICTC) 2018, pp.1417-1419
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- In this paper, objectivity based self-evolving agent model validation is presented for house market simulation. The self-evolving simulation updates agent models using verification data. However, because there is no verification data for the future, it is difficult to predict the future with self-evolving module accurately. Therefore, even if simulation is performed using a self-evolving mechanism, validation of the agent model is still important in order to obtain correct prediction results for the future. Verification of objectivity is carried out in the procedure of comparing the simulation prediction value with the past actual data, and it is judged that the result of the simulation is valid if it shows a form similar to the past actual data. The error rate and correlation between the verification data and simulation results are calculated through the root mean square error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination. The accuracy of the simulation results for the apartment price index and 2-year-lease index are approximately 95% and 89%, respectively, and coefficient of determination are 0.507 and 0.753, respectively. Therefore, self-evolving agent based model designed for house market simulation can be said to have objectivity.
- KSP Keywords
- Agent model, Coefficient of determination, Market simulation, Model Validation, Price index, Root mean square(RMS), Simulation prediction, Social issues, Verification data, agent-based model(ABM), error rate