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An Agent-Oriented Group Decision Architecture

  • Liang XiaoEmail author
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 148)

Abstract

Group decisions are useful and crucial across socio-technical contexts, but there is a lack of generic, systematic, and comprehensive architecture that can support decision-making practically. In this paper, we propose an agent-oriented group decision architecture. It provides separate but unified representation formalisms for both global interaction protocols and local decision rules. An accompanied runtime coordination mechanism is offered, as well as an engine for agent interpretation of global and local levels of interactions towards decision-making. The architecture is general enough for group decision-making across disciplines.

Keywords

Agent Group decision-making Protocol Rule 

References

  1. 1.
    Smith, S., Agrawal, N., Tsay, A.: A decision support system for retail supply chain planning for private-label merchandise with multiple vendors. In: Geunes, J., Pardalos, P., Romeijn, H. (eds.) Supply Chain Management Model, Applications, and Research Directions, pp. 163–198. Kluwer, Dordrecht (2003)Google Scholar
  2. 2.
    Lee, H.L., Whang, S.: Demand chain excellence: a tale of two retailers. Supply Chain Manag. Rev. 5(3), 40–46 (2001)Google Scholar
  3. 3.
    Fox, J., Cooper, R.P., Glasspool, D.W.: A canonical theory of dynamic decision-making. Front. Psychol. 4, 150 (2013)Google Scholar
  4. 4.
    Xiao, L., Fox, J.: Towards an agent-oriented framework for multidisciplinary decision support and its application to triple assessment of breast cancer. In: Proceedings of the 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC 2017), vol. 1, pp. 97–102. IEEE Press (2017)Google Scholar
  5. 5.
    Wooldridge, M.: An Introduction to Multiagent Systems. Wiley, New York (2008)Google Scholar
  6. 6.
    Rao, A.S., Georgeff, M.P.: BDI agents: from theory to practice. In: Proceedings of the 1st International Conference on Multi-Agent Systems, pp. 312–319 (1995)Google Scholar
  7. 7.
    Wooldridge, M., Jennings, N.R., Kinny, D.: The Gaia methodology for agent-oriented analysis and design. Auton. Agents Multi-Agent Syst. 3, 285–312 (2000)CrossRefGoogle Scholar
  8. 8.
    Bresciani, P., Perini, A., Giorgini, P., Giunchiglia, F., Mylopoulos, J.: Tropos: an agent-oriented software development methodology. Auton. Agent Multi Agent Syst. 8, 203–236 (2004)CrossRefGoogle Scholar
  9. 9.
    Yu, E.: Modelling strategic relationships for process reengineering. In: Social Modeling for Requirements Engineering, vol. 11 (2011)Google Scholar
  10. 10.
    Dardenne, A., Lamsweerde, A., Fickas, S.: Goal-directed requirements acquisition. Sci. Comput. Program. 20, 3–50 (1993)CrossRefGoogle Scholar
  11. 11.
    DeSanctis, G., Gallupe, R.B.: Group decision support systems: a new frontier. ACM SIGMIS Database 16(2), 3–10 (1984)CrossRefGoogle Scholar
  12. 12.
    DeSanctis, G., Gallupe, R.B.: A foundation for the study of group decision support systems. Manag. Sci. 33, 589–609 (1987)CrossRefGoogle Scholar
  13. 13.
    Alonso, S., Herrera-Viedma, E., Chiclana, F., Herrera, F.: A web based consensus support system for group decision making problems and incomplete preferences. Inf. Sci. 180, 4477–4495 (2010). ElsevierMathSciNetCrossRefGoogle Scholar
  14. 14.
    Marreiros, G., Santos, R., Ramos, C., Neves, J.: Context-aware emotion-based model for group decision making. IEEE Intell. Syst. 25, 31–39 (2010)CrossRefGoogle Scholar
  15. 15.
    Carneiro, J., Saraiva, P., Martinho, D., Marreiros, G., Novais, P.: Representing decision-makers using styles of behavior: an approach designed for group decision support systems. Cogn. Syst. Res. 47, 109–132 (2018). ElsevierCrossRefGoogle Scholar
  16. 16.
    Kim, Y., Matson, E.T.: A realistic decision making for task allocation in heterogeneous multi-agent systems. Proc. Comput. Sci. 94, 386–391 (2016)CrossRefGoogle Scholar
  17. 17.
    Marcon, E., Chaabane, S., Sallez, Y., Bonte, T., Trentesaux, D.: A multi-agent system based on reactive decision rules for solving the caregiver routing problem in home health care. Simul. Model. Pract. Theory 74, 134–151 (2017). ElsevierCrossRefGoogle Scholar
  18. 18.
    Vahidov, R., Fazlollahi, B.: Pluralistic multi-agent decision support system: a framework and an empirical test. Inf. Manag. 41(7), 883–898 (2004). ElsevierCrossRefGoogle Scholar
  19. 19.
    Xiao, L., Cousins, G., Courtney, B., Hederman, L., Fahey, T., Dimitrov, B.D.: Developing an Electronic Health Record (EHR) for methadone treatment recording and decision support. BMC Med. Inform. Decis. Mak. 11, 5 (2011)CrossRefGoogle Scholar
  20. 20.
    Xiao, L., Cousins, G., Fahey, T., Dimitrov, B., Hederman, L.: Developing a rule-driven clinical decision support system with an extensive and adaptive architecture. In: Proceedings of the 14th International Conference on E-health Networking, Application & Services (HealthCom’2012), pp. 250–254 (2012)Google Scholar
  21. 21.
    Robertson, D.: A lightweight method for coordination of agent oriented web services. In: Proceedings of AAAI Spring Symposium on Semantic Web Services, Stanford (2004)Google Scholar
  22. 22.
    Robertson, D.: A lightweight coordination calculus for agent systems. LNCS, vol. 3476, pp. 183–197. Springer, Berlin (2005)CrossRefGoogle Scholar
  23. 23.
    Xiao, L., Robertson, D., Croitoru, M., Lewis, P., Dashmapatra, S., Dupplaw, D., Hu, B.: Adaptive agent model: an agent interaction and computation model. In: Proceedings of the 31st IEEE Annual International Computer Software and Applications Conference (COMPSAC’07), vol. II, pp. 153–158. IEEE Computer Society (2007)Google Scholar
  24. 24.
    Xiao, L., Lewis, P., Gibb, A.: Developing a security protocol for a distributed decision support system in a healthcare environment. In: Proceedings of the 30th International Conference on Software Engineering (ICSE’08), pp. 673–682. ACM, New York (2008)Google Scholar
  25. 25.
    Xiao, L.: An agent-oriented data sharing and decision support service for hubei provincial care platform. In: Proceedings of the 9th Multi-Disciplinary International Workshop on Artificial Intelligence (MIWAI 2015). LNAI, vol. 9426, pp. 429–440. Springer, Cham (2015)Google Scholar
  26. 26.
    Murray-Rust, D., Robertson, D.: LSCitter: building social machines by augmenting existing social networks with interaction models. In: Proceedings of the 23rd International Conference on World Wide Web, pp. 875–880. ACM, New York (2014)Google Scholar
  27. 27.
    Meira, S., et al.: The emerging web of social machines. In: Proceedings of the 35th Annual Computer Software and Applications Conference, pp. 26–27. IEEE (2011)Google Scholar
  28. 28.
    Robertson, D., Giunchiglia, F.: Programming the social computer. Philos. Trans. Eng. Sci. A Math. Phys. 371(1987), 20120379 (2013)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Hubei University of TechnologyWuhanChina

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