Dynamic System of Rating Alternatives by Agents with Interactions

Conference paper
First Online:
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 58)

Abstract

Business process simulation models usually incorporate several essential components that reflect customer behavior for modeling system inputs and outputs and ranking and/or rating given alternatives. In this paper we deal with a dynamic system of rating given number of alternatives based on agent-based simulation with interactions among agents which is based on a set of parameters and on pairwise comparisons method. Our system is able to replicate various examples of processes, e.g. financial market evaluation, evaluation of products’ demand and supply, evaluation of political parties in general elections, evaluation of universities etc. A simple simulation experiment is presented and discussed.

Keywords

Dynamic system Agents Ranking alternatives Pairwise comparison matrix Simulation 
This is a preview of subscription content, log in to check access.

Notes

Acknowledgments

This paper was supported by the Ministry of Education, Youth and Sports Czech Republic within the Institutional Support for Long-term Development of a Research Organization in 2016.

References

  1. 1.
    Axelrod, R.: The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press, Princeton, NJ (1997)Google Scholar
  2. 2.
    Anthony, P., Jennings, N.R.: Evolving bidding strategies for multiple auctions. In: Proceedings of 15th European Conference on Artificial Intelligence, pp. 182–187. Netherlands (2002)Google Scholar
  3. 3.
    Walsh, W.E., et al.: Analyzing complex strategic interactions in multi-agent games. In: Proceedings of AAAI Workshop on Game-Theoretic and Decision-Theoretic Agents (2002)Google Scholar
  4. 4.
    Dumas, M., La Rosa, M., Mendling, J., Reijers, H.: Fundamentals of Business Process Management. Springer, Berlin (2013)CrossRefGoogle Scholar
  5. 5.
    Bonabeau, E.: Agent-based modeling: methods and techniques for simulating human systems. PNAS 99, 7280–7287 (2002)CrossRefGoogle Scholar
  6. 6.
    Barnett, M.: Modeling and simulation in business process management (2013). http://news.bptrends.com/publicationfiles
  7. 7.
    Sperka, R., Spisak, M.: Transaction costs influence on the stability of financial market: agent-based simulation. J. Bus. Econ. Manage. 14(Supplement 1), S1–S12 (2013)CrossRefGoogle Scholar
  8. 8.
    Wooldridge, M.: MultiAgent Systems: An Introduction, 2nd edn. Wiley, Chichester (2009)Google Scholar
  9. 9.
    Ramik, J.: Pairwise comparison matrix with fuzzy elements on alo-group. Inf. Sci. 297, 236–253 (2015)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Saaty, T.L.: Multicriteria Decision Making—the Analytical Hierarchy Process, vol. I. RWS Publications, Pittsburgh (1991)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Faculty of Business Administration in KarvináSilesian University in OpavaKarvináCzech Republic

Personalised recommendations