Skip to main content
SpringerLink
Log in

CFBM - A Framework for Data Driven Approach in Agent-Based Modeling and Simulation

  • Conference paper
  • First Online:
Nature of Computation and Communication (ICTCC 2016)

Included in the following conference series:

Abstract

Recently, there has been a shift from modeling driven approach to data driven approach in Agent Based Modeling and Simulation (ABMS). This trend towards the use of data-driven approaches in simulation aims at using more and more data available from the observation systems into simulation models [1, 2]. In a data driven approach, the empirical data collected from the target system are used not only for the design of the simulation models but also in initialization, evaluation of the output of the simulation platform. That raises the question how to manage empirical data, simulation data and compare those data in such agent-based simulation platform.

In this paper, we first introduce a logical framework for data driven approach in agent-based modeling and simulation. The introduced framework is based on the combination of Business Intelligence solution and a multi-agent based platform called CFBM (Combination Framework of Business intelligence and Multi-agent based platform). Secondly, we demonstrate the application of CFBM for data driven approach via the development of a Brown Plant Hopper Surveillance Models (BSMs), where CFBM is used not only to manage and integrate the whole empirical data collected from the target system and the data produced by the simulation model, but also to initialize and validate the models.

The successful development of the CFBM consists not only in remedying the limitation of agent-based modeling and simulation with regard to data management but also in dealing with the development of complex simulation systems with large amount of input and output data supporting a data driven approach.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://github.com/gama-platform/gama/wiki.

  2. 2.

    http://www.olap4j.org/.

  3. 3.

    http://msdn.microsoft.com/en-us/library/ms145514.aspx.

  4. 4.

    https://github.com/gama-platform/gama/wiki/G__UsingDatabase.

  5. 5.

    http://www.vietnam.ird.fr/les-activites/renforcement-des-capacites/jeunes-equipes-aird/jeai-dream-umi-209-ummisco-2011-2013.

References

  1. Edmonds, B., Moss, S.: From KISS to KIDS – an ‘anti-simplistic’ modelling approach. In: Davidsson, P., Logan, B., Takadama, K. (eds.) MABS 2004. LNCS (LNAI), vol. 3415, pp. 130–144. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  2. Hassan, S.: Towards a Data-driven Approach for Agent-Based Modelling: Simulating Spanish (2009)

    Google Scholar 

  3. Becu, N., Perez, P., Walker, A., Barreteau, O., Page, C.L.: Agent based simulation of a small catchment water management in Northern Thailand. Ecol. Modell. 170, 319–331 (2003)

    Article  Google Scholar 

  4. Gaudou, B., Sibertin-Blanc, C., Therond, O., Amblard, F., Arcangeli, J.-P., Balestrat, M., Charron-Moirez, M.-H., Gondet, E., Hong, Y., Louail, T., Mayor, E., Panzoli, D., Sauvage, S., Sanchez-Perez, J.-M., Taillandier, P., Nguyen, V.B., Vavasseur, M., Mazzega, P.: The maelia multi-agent platform for integrated assessment of low-water management issues. In: Multi-Agent-Based Simulation XIV-International Workshop, MABS (2013)

    Google Scholar 

  5. Rao, D.M., Chernyakhovsky, A., Rao, V.: Modeling and analysis of global epidemiology of avian influenza. Environ. Model Softw. 24, 124–134 (2009)

    Article  Google Scholar 

  6. Stroud, P., Valle, S. Del, Sydoriak, S., Riese, J., Mniszewski, S.: Spatial dynamics of pandemic influenza in a massive artificial society. Artif. Soc. Soc. Simul. 10 (2007)

    Google Scholar 

  7. Amouroux, E., Desvaux, S., Drogoul, A.: Towards virtual epidemiology: an agent-based approach to the modeling of H5N1 propagation and persistence in North-Vietnam. In: Bui, T.D., Ho, T.V., Ha, Q.T. (eds.) PRIMA 2008. LNCS (LNAI), vol. 5357, pp. 26–33. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  8. Dunham, J.: An agent-based spatially explicit epidemiological model in MASON. J. Artif. Soc. Soc. Simul. 9 (2005)

    Google Scholar 

  9. Sibertin-Blanc, C., Roggero, P., Adreit, F., Baldet, B., Chapron, P., El-Gemayel, J., Mailliard, M., Sandri, S.: SocLab: A Framework for the modeling, simulation and analysis of power in social organizations. J. Artif. Soc. Soc. Simul. 16 (2013)

    Google Scholar 

  10. Barnaud, C., Bousquet, F., Trebuil, G.: Multi-agent simulations to explore rules for rural credit in a highland farming community of Northern Thailand. Ecol. Econ. 66, 615–627 (2008)

    Article  Google Scholar 

  11. Hassan, S., Antunes, L., Pavón, J.: Mentat: a data-driven agent-based simulation of social values evolution. In: Di Tosto, G., Van Dyke Parunak, H. (eds.) MABS 2009. LNCS, vol. 5683, pp. 135–146. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  12. Hassan, S., Pavon, J., Gilbert, N.: Injecting data into simulation: can agent-based modelling learn from microsimulation? In: The World Congress of Social Simulation 2008, Washington, D.C. (2008)

    Google Scholar 

  13. Hassan, S., Pavón, J., Antunes, L., Gilbert, N.: Injecting data into agent-based simulation. In: Takadama, K., Cioffi-Revilla, C., Deffuant, G. (eds.) Simulating Interacting Agents and Social Phenomena. Agent-Based Social Systems, vol. 7, pp. 177–191. Springer, Japan (2010)

    Google Scholar 

  14. Gilbert, N., Troitzsch, K.G.: Simulation for the Social Scientist. Open University Press, Buckingham (2005)

    Google Scholar 

  15. Mahboubi, H., Faure, T., Bimonte, S., Deffuant, G., Chanet, J.-P., Pinet, F.: A multidimensional model for data warehouses of simulation results. Int. J. Agric. Environ. Inf. Syst. 1, 1–19 (2010)

    Article  Google Scholar 

  16. Vasilakis, C., El-Darzi, E.: A data warehouse environment for storing and analyzing simulation output data. In: Simulation Conference (2004)

    Google Scholar 

  17. Inmon, W.H.: Building the Data Warehouse. Wiley Publishing Inc. (2005)

    Google Scholar 

  18. Kimball, R., Ross, M.: The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling. John Wiley & Sons Inc., New York (2002)

    Google Scholar 

  19. Madeira, H., Costa, J.P., Vieira, M.: 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 (2003)

    Google Scholar 

  20. Sosnowski, J., Zygulski, P., Gawkowski, P.: Developing data warehouse for simulation experiments. In: Kryszkiewicz, M., Peters, J.F., Rybiński, H., Skowron, A. (eds.) RSEISP 2007. LNCS (LNAI), vol. 4585, pp. 543–552. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  21. Ehmke, J.F., Grosshans, D., Mattfeld, D.C., Smith, L.D.: Interactive analysis of discrete-event logistics systems with support of a data warehouse. Comput. Ind. 62, 578–586 (2011)

    Article  Google Scholar 

  22. Vasilakis, C., El-Darzi, E., Chountas, P.: A decision support system for measuring and modelling the multi-phase nature of patient flow in hospitals. In: Chountas, P., Petrounias, I., Kacprzyk, J. (eds.) Intelligent Techniques and Tools for Novel System Architectures. SCI, vol. 109, pp. 201–217. Springer, Heidelberg (2008)

    Google Scholar 

  23. Mahboubi, H., Faure, T., Bimonte, S., Deffuant, G., Chanet, J.P., Pinet, F.: A multidimensional model for data warehouses of simulation results. Int. J. Agric. Environ. Inf. Syst. 1, 1–19 (2010)

    Article  Google Scholar 

  24. Hassan, S., Antunes, L., Pavon, J., Gilbert, N.: Stepping on earth: a roadmap for data-driven agent-based modelling. In: The 5th Conference of the European Social Simulation Association (ESSA 2008), pp. 1–12 (2008)

    Google Scholar 

  25. Truong, T.M., Truong, V.X., Amblard, F., Sibertin-blanc, C., Drogoul, A., Le, M.N.: An Implementation of framework of business intelligence for agent-based simulation. In: The 4th International Symposium on Information and Communication Technology (SoICT 2013), pp. 35–44. ACM (2013)

    Google Scholar 

  26. Kimball, R., Ross, M.: Data Warehouse Toolkit: The Complete Guide to Dimentional Modeling. John Wiley & Sons Inc., New York (2002)

    Google Scholar 

  27. Ngo, T.D.: Simulating the flooding progression by the influence of rainfall in Can Tho city (2013)

    Google Scholar 

  28. Truong, V.X.: Optimization by simulation of an environmental surveillance network - application to the fight against rice pests in the mekong delta (vietnam) (2014)

    Google Scholar 

  29. Truong, T.M., Amblard, F., Benoit, G., Sibertin-blanc, C.: To calibrate & validate an agent-based simulation model an application of the combination framework of bi solution & multi-agent platform. In: The 6th International Conference on Agents and Artificial Intelligence (ICAART 2014), pp. 172–183 (2014)

    Google Scholar 

  30. Phan, C.H., Huynh, H.X., Drogoul, A.: An agent-based approach to the simulation of Brown Plant Hopper (BPH) invasions in the Mekong Delta. In: 2010 IEEE RIVF International Conference on Computing and Communication Technologies, Research, Innovation, and Vision for the Future (RIVF), pp. 1–6. IEEE (2010)

    Google Scholar 

  31. Truong, V.X., Drogoul, A., Huynh, H.X., Le, M.N.: Modeling the brown plant hoppers surveillance network using agent-based model - application for the Mekong Delta region. In: Proceedings of the Second Symposium on Information and Communication Technology, pp. 127–136. ACM (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. CIT, Can Tho University, Can Tho, Vietnam

    Thai Minh Truong

  2. UMR 5505 CNRS-IRIT, Université Toulouse 1 Capitole, Toulouse, France

    Thai Minh Truong, Frédéric Amblard, Benoit Gaudou & Christophe Sibertin Blanc

Authors
  1. Thai Minh Truong
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Frédéric Amblard
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Benoit Gaudou
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Christophe Sibertin Blanc
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Thai Minh Truong .

Editor information

Editors and Affiliations

  1. Nguyen Tat Thanh University , Ho Chi Minh City, Vietnam

    Phan Cong Vinh

  2. Fukuoka Institute of Technology , Fukuoka, Japan

    Leonard Barolli

Rights and permissions

Reprints and permissions

Copyright information

© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Cite this paper

Truong, T.M., Amblard, F., Gaudou, B., Blanc, C.S. (2016). CFBM - A Framework for Data Driven Approach in Agent-Based Modeling and Simulation. In: Vinh, P., Barolli, L. (eds) Nature of Computation and Communication. ICTCC 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 168. Springer, Cham. https://doi.org/10.1007/978-3-319-46909-6_24

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-46909-6_24

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46908-9

  • Online ISBN: 978-3-319-46909-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation