Agent-Based Modelling and Simulations as an Integral Functionality of the Business Intelligence Framework

  • Vladimír BurešEmail author
  • Petr Blecha
  • Petr Tučník
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 538)


The Business Intelligence concept has been subject of interest in the realm of computer science and business administration for several years. While various analytical tools have been developed and focus on historical data has represented the main stream of research, inclusion of simulations-based forecasts and predictions have been somehow neglected. Therefore, this paper introduces the business intelligence framework in association with agent-based simulations. Moreover, it supports it with the demonstration, in which particular functionality of the Broker agent is used. Finally, the paper also depicts possibilities of further research that can elaborate and further progress the use of agent-based simulations in business intelligence.


Agent Broker Business intelligence Virtual economy Economic model 



The support of the FIM UHK Specific Research Project “SCM and Control of Markets and Production in Agent-based Computational Economics” is gratefully acknowledged.


  1. 1.
    Bargigli, L., Tedeschi, G.: Major trends in agent-based economics. J. Econ. Interac. Coord. 8(2), 211–217 (2013)CrossRefGoogle Scholar
  2. 2.
    Bunata, E.: Using business intelligence to manage supply costs. Healthc. Finan. Manag. J. Healthc. Finan. Manag. Assoc. 67(8), 44–47 (2013)Google Scholar
  3. 3.
    Bureš, V., Otčenášková, T., Čech, P., Antoš, K.: A proposal for a computer-based framework of support for public health in the management of biological incidents: The Czech Republic experience. Perspect. Public Health 132(6), 292–298 (2012)CrossRefGoogle Scholar
  4. 4.
    Bureš, V., Tučník, P.: Complex agent-based models: application of a constructivism in the economic research. E M Ekonomie a Manag. 17(3), 152–168 (2014)CrossRefGoogle Scholar
  5. 5.
    Damaceanu, R.-C., Capraru, B.-S.: Implementation of a multi-agent computational model of retail banking market using netlogo. Metalurgia Int. 17(5), 230–236 (2012)Google Scholar
  6. 6.
    Dosi, G., Fagiolo, G., Roventini, A.: The microfoundations of business cycles: an evolutionary, multi-agent model. Schumpeterian Perspect. Innov. Competition Growth 18(3–4), 413–432 (2009)zbMATHGoogle Scholar
  7. 7.
    Guessoum, Z., Rejeb, L., Durand, R.: Using adaptive multi-agent systems to simulate economic models. In: Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, vol. 1, pp. 68–75 (2004)Google Scholar
  8. 8.
    Janssen, M., de Vries, B.: The battle of perspectives: a multi-agent model with adaptive responses to climate change. Ecol. Econ. 26(1), 43–65 (1998)CrossRefGoogle Scholar
  9. 9.
    Lee, C.K., Lau, H.C., Ho, G.T., Ho, W.: Design and development of agent-based procurement system to enhance business intelligence. Expert Syst. Appl. 36(1), 877–884 (2009)CrossRefGoogle Scholar
  10. 10.
    Leonard, A., Masson, M., Mitchell, T., Moss, J., Ufford, M.: SQL Server Integration Services Design Patterns. Apress, New York (2014)CrossRefGoogle Scholar
  11. 11.
    Lipika, D., Ishan, V.: Text-driven reasoning and multi-structured data analytics for business intelligence. In: Integration of Data Mining in Business Intelligence Systems, pp. 143–173 (2015)Google Scholar
  12. 12.
    Michalewicz, Z., Schmidt, M., Michalewicz, M., Chiriac, C.: Adaptive business intelligence: three case studies. Evolutionary Computation in Dynamic and Uncertain Environments, pp. 179–196. Springer, Berlin (2007)CrossRefGoogle Scholar
  13. 13.
    Petermann, A., Junghanns, M., Müller, R., Rahm, E.: Graph-based data integration and business intelligence with BIIIG. In: Proceedings of the VLDB Endowment, 7(13) (2014)CrossRefGoogle Scholar
  14. 14.
    Rao, M., Jain, M.B., Shukla, P.: The use of multi agent paradigm to build an agent based architecture for e-commerce application. Res. J. Eng. Technol. 2(1), 5–9 (2011)Google Scholar
  15. 15.
    Singh, A., Mishra, P.K., Jain, R., Khurana, M.K.: Design of global supply chain network with operational risks. Int. J. Adv. Manuf. Technol. 60(1–4), 273–290 (2012)CrossRefGoogle Scholar
  16. 16.
    Tučník, P., Bureš, V.: Inclusion of complexity: modelling enterprise business environment by means of agent-based simulation. Int. Rev. Model. Simul. 6(5), 1709–1717 (2013)Google Scholar
  17. 17.
    Vidal, J.M., Durfee, E.H.: Learning nested agent models in an information economy. J. Exp. Theor. Artif. Intell. 10(3), 291–308 (1998)CrossRefGoogle Scholar
  18. 18.
    Wilkinson, I.F., Young, L.C.: The past and the future of business marketing theory. Ind. Mark. Manag. 42(3), 394–404 (2013)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.University of Hradec KraloveHradec KraloveCzech Republic

Personalised recommendations