Requests Management for Smartphone-Based Matching Applications Using a Multi-agent Approach

  • Gilles SimoninEmail author
  • Barry O’Sullivan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10079)


We present a new multi-agent approach to managing how requests are sent between users of smartphone-based applications for reaching bi-lateral agreements. Each agent is modelled as having a selfish behaviour based on his preferences and an altruist behaviour with respect to the links between the agent and his neighbours. The objective is to maximise the likelihood of an acceptable match while minimising the burden on the users due to unnecessary messaging. We provide a dynamic algorithm using this architecture and we present an empirical evaluation with various mathematical models of user behaviour and altruism. The evaluation shows that our approach can reduce the risks of rejections and the number of requests while increasing the likelihood of acceptable matches.



This paper has emanated from research conducted with the financial support of Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289 and from industry partner Carma (


  1. 1.
    Balch, T., Arkin, R.: Communication in reactive multi-agent robotic systems. Autonom. Robots 1, 27–52 (1994)CrossRefGoogle Scholar
  2. 2.
    Chapelle, J., Simonin, O., Ferber, J.: How situated agents can learn to cooperate by monitoring their neighbors’ satisfaction. In: ECAI, pp. 68–72 (2002)Google Scholar
  3. 3.
    Grinshpoun, T., Grubshtein, A., Zivan, R., Netzer, A., Meisels, A.: Asymmetric distributed constraint optimization problems. J.Artif. Intell. Res. 47, 613–647 (2013)MathSciNetzbMATHGoogle Scholar
  4. 4.
    Hilaire, V., Gruer, P., Koukam, A., Simonin, O.: Formal driven prototyping approach for multiagent systems. Int. J. Agent-Orient. Softw. Eng. 2(2), 246–266 (2008)CrossRefGoogle Scholar
  5. 5.
    Hirayama, K., Yokoo, M.: The distributed breakout algorithms. Artif. Intell. 161(1–2), 89–115 (2005)MathSciNetCrossRefzbMATHGoogle Scholar
  6. 6.
    Maheswaran, R.T., Pearce, J.P., Tambe, M.: A family of graphical-game-based algorithms for distributed constraint optimization problems. In: Scerri, P., Vincent, R., Mailler, R. (eds.) Coordination of Large-Scale Multiagent Systems, pp. 127–146. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  7. 7.
    Mataric, M.J.: Behaviour-based control: examples from navigation, learning, and group behaviour. J. Exp. Theor. Artif. Intell. 9(2–3), 323–336 (1997)CrossRefGoogle Scholar
  8. 8.
    Lucidarme, P., O.S., Liégeois, A.: Implementation and evaluation of a satisfaction/altruism based architecture for multi-robot systems. In: IEEE International Conference on Robotics and Automation, vol. 1, pp. 1007–1012 (2002)Google Scholar
  9. 9.
    Simonin, G., O’Sullivan, B.: Optimisation for the ride-sharing problem: a complexity-based approach. In: ECAI, pp. 831–836 (2014)Google Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Insight Centre for Data Analytics, Department of Computer ScienceUniversity College CorkCorkIreland

Personalised recommendations