To Calibrate & Validate an Agent-based Simulation Model - An Application of the Combination Framework of BI Solution & Multi-agent Platform
Thai Minh Truong, Frédéric Amblard, Benoit Gaudou, Christophe Sibertin Blanc
2014
Abstract
Integrated environmental modeling approaches, especially the agent-based modeling one, are increasingly used in large-scale decision support systems. A major consequence of this trend is the manipulation and generation of huge amount of data in simulations, which must be efficiently managed. Furthermore, calibration and validation are also challenges for Agent-Based Modelling and Simulation (ABMS) approaches when the model has to work with integrated systems involving high volumes of input/output data. In this paper, we propose a calibration and validation approach for an agent-based model, using a Combination Framework of Business intelligence solution and Multi-agent platform (CFBM). The CFBM is a logical framework dedicated to the management of the input and output data in simulations, as well as the corresponding empirical datasets in an integrated way. The calibration and validation of Brown Plant Hopper Prediction model are presented and used throughout the paper as a case study to illustrate the way CFBM manages the data used and generated during the life-cycle of simulation and validation.
References
- Amblard, F., Bommel, P., Rouchier, J., 2007. Assessment and Validation of Multi-agent Models. In: Phan, D., Amblard, F. (Eds.), Agent-Based Modelling and Simulation in The Social and Human Sciences. The Bardwell Press, Oxford, pp. 93-114.
- ASTM, 1984. Standard Practice for Evaluating Environmental Fate Models of Chemicals. American Society of Testing Materials. Philadelphia.
- Crooks, A., Castle, C., Batty, M., 2008. Key challenges in agent-based modelling for geo-spatial simulation. Comput. Environ. Urban Syst. 32, 417-430.
- Crooks, A. T., Heppenstall, A. J., 2012. Introduction to Agent-Based Modeling. In: Heppenstall, A.J., Crooks, A. T., See, L. M., Batty, M. (Eds.), Agent-Based Models of Geographical Systems. Springer Netherlands, Dordrecht, pp. 85-105.
- Donigian, A. S., 2002. Watershed model calibration and validation: The HSPF experience. In: Water Environment Federation. pp. 44-73.
- Ehmke, J. F., Grosshans, D., Mattfeld, D. C., Smith, L. D., 2011. Interactive analysis of discrete-event logistics systems with support of a data warehouse. Comput. Ind. 62, 578-586.
- Inmon, W. H., 2005. Building the Data Warehouse, 4th ed. Wiley Publishing Inc.
- Jaccard, P., 1908. Nouvelles recherches sur la distribution florale. Bull Soc. Vaud. Sci. Nat 223-270.
- Kimball, R., Ross, M., 2002. The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling, 2nd ed. John Wiley & Sons, Inc.
- Klügl, F., 2008. A validation methodology for agent-based simulations. In: Proceedings of the 2008 ACM Symposium on Applied Computing. pp. 39-43.
- Laniak, G. F., Rizzoli, A. E., Voinov, A., 2013. Thematic issue on the future of integrated modeling science and technology. Environ. Model. Softw. 39, 13-23.
- Law, A. M., 2009. How to build valid and credible simulation models. In: Simulation Conference (WSC), Proceedings of the 2009 Winter. IEEE, pp. 24-33.
- Madeira, H., Costa, J. P., Vieira, M., 2003. The OLAP and data warehousing approaches for analysis and sharing of results from dependability evaluation experiments. In: International Conference on Dependable Systems and Networks. pp. 86-99.
- Mahboubi, H., Faure, T., Bimonte, S., Deffuant, G., Chanet, J. P., Pinet, F., 2010. A Multidimensional Model for Data Warehouses of Simulation Results. Int. J. Agric. Environ. Inf. Syst. 1, 1-19.
- Ngo, T. A., See, L., 2012. Calibration and Validation of Agent-Based Models of Land Cover Change. In: Heppenstall, A. J., Crooks, A. T., See, L. M., Batty, M. (Eds.), Agent-Based Models of Geographical Systems. Springer Netherlands, pp. 181-197.
- Niwattanakul, S., Singthongchai, J., Naenudorn, E., Wanapu, S., 2013. Using of Jaccard Coefficient for Keywords Similarity. In: International MultiConference of Engineers and Computer Scientists. pp. 380-384.
- Phan, C. H., Huynh, H. X., Drogoul, A., 2010. An agentbased approach to the simulation of Brown Plant Hopper (BPH) invasions in the Mekong Delta. In: Computing and Communication Technologies, Research, Innovation, and Vision for the Future (RIVF), 2010 IEEE RIVF International Conference. IEEE, pp. 1-6.
- Rahman, M., Hassan, M. R., Buyya, R., 2010. Jaccard Index based availability prediction in enterprise grids. In: Procedia Computer Science. Elsevier, pp. 2707-2716.
- Rogers, A., Tessin, P. von, 2004. Multi-objective calibration for agent-based models.
- Sachdeva, V., Freimuth, D., Mueller, C., 2009. Evaluating the jaccard-tanimoto index on multi-core architectures. In: Computational Science-ICCS 2009. Springer Berlin Heidelberg, pp. 944-953.
- Said, L. B., Bouron, T., Drogoul, A., 2002. Agent-based interaction analysis of consumer behavior. In: The First International Joint Conference on Autonomous Agents and Multiagent Systems: Part 1. ACM. pp. 184-190.
- Sosnowski, J., Zygulski, P., Gawkowski, P., 2007. Developing Data Warehouse for Simulation Experiments. In: Rough Sets and Intelligent Systems Paradigms. Springer Berlin Heidelberg, pp. 543-552.
- Truong, T. M., Truong, V. X., Amblard, F., Drogoul, A., Benoit, G., Huynh, H. X., Le, M. N., Sibertin-blanc, C., 2013. An implementation of framework of Business Intelligence for Agent-based Simulation. In: The 4th International Symposium on Information and Communication Technology (SoICT 2013).
- Truong, V. X., Huynh, H. X., Le, M. N., Drogoul, A., 2013. Optimizing an Environmental Surveillance Network with Gaussian Process - An optimization approach by agent-based simulation. In: The Sixth International KES Conference on Agents and MultiAgent Systems - Technologies and Applications (KES AMSTA 2013). IOS Press, pp. 102-111.
- Vasilakis, C., El-Darzi, E., Chountas, P., 2008. A decision support system for measuring and modelling the multiphase nature of patient flow in hospitals. In: Intelligent Techniques and Tools for Novel System Architectures. Springer Berlin Heidelberg, pp. 201-217.
- Willmott, C. J., Ackleson, S. G., Davis, R. E., Feddema, J. J., Klink, K. M., Legates, D. R., O'Donnell, J., Rowe, C. M., 1985. Statistics for the evaluation and comparison of models. J. Geophys. Res. 90, 8995- 9005.
- Wolda, H., 1981. Similarity indices, sample size and diversity. Oecologia 50.3, 296-302.
Paper Citation
in Harvard Style
Minh Truong T., Amblard F., Gaudou B. and Sibertin Blanc C. (2014). To Calibrate & Validate an Agent-based Simulation Model - An Application of the Combination Framework of BI Solution & Multi-agent Platform . In Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-016-1, pages 172-183. DOI: 10.5220/0004820401720183
in Bibtex Style
@conference{icaart14,
author={Thai Minh Truong and Frédéric Amblard and Benoit Gaudou and Christophe Sibertin Blanc},
title={To Calibrate & Validate an Agent-based Simulation Model - An Application of the Combination Framework of BI Solution & Multi-agent Platform },
booktitle={Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2014},
pages={172-183},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004820401720183},
isbn={978-989-758-016-1},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - To Calibrate & Validate an Agent-based Simulation Model - An Application of the Combination Framework of BI Solution & Multi-agent Platform
SN - 978-989-758-016-1
AU - Minh Truong T.
AU - Amblard F.
AU - Gaudou B.
AU - Sibertin Blanc C.
PY - 2014
SP - 172
EP - 183
DO - 10.5220/0004820401720183