A Coalitional Algorithm for Recursive Delegation

  • Juan AfanadorEmail author
  • Nir Oren
  • Murilo S. Baptista
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11873)


Within multi-agent systems, some agents may delegate tasks to other agents for execution. Recursive delegation designates situations where delegated tasks may, in turn, be delegated onwards. In unconstrained environments, recursive delegation policies based on quitting games are known to outperform policies based on multi-armed bandits. In this work, we incorporate allocation rules and rewarding schemes when considering recursive delegation, and reinterpret the quitting-game approach in terms of coalitions, employing the Shapley and Myerson values to guide delegation decisions. We empirically evaluate our extensions and demonstrate that they outperform the traditional multi-armed bandit based approach, while offering a resource efficient alternative to the quitting-game heuristic.


  1. 1.
    Afanador, J., Baptista, M., Oren, N.: An adversarial algorithm for delegation. In: Lujak, M. (ed.) AT 2018. LNCS (LNAI), vol. 11327, pp. 130–145. Springer, Cham (2019). Scholar
  2. 2.
    Alonso, R., Matouschek, N.: Optimal delegation. Rev. Econ. Stud. 75(1), 259–293 (2008)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Brezzi, M., Lai, T.L.: Optimal learning and experimentation in bandit problems. J. Econ. Dyn. Control 27(1), 87–108 (2002)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Castelfranchi, C., Falcone, R.: Towards a theory of delegation for agent-based systems. Robot. Autonomous Syst. 24(3–4), 141–157 (1998). Scholar
  5. 5.
    Chen, H., Ta, S., Sun, B.: Cooperative game approach to power allocation for target tracking in distributed mimo radar sensor networks. IEEE Sens. J. 15(10), 5423–5432 (2015)CrossRefGoogle Scholar
  6. 6.
    Etuk, A., Norman, T.J., Oren, N., Sensoy, M.: Strategies for truth discovery under resource constraints. In: Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, pp. 1807–1808. International Foundation for Autonomous Agents and Multiagent Systems (2015)Google Scholar
  7. 7.
    Kruschke, J.K.: Bayesian estimation supersedes the t test. J. Exp. Psychol. Gen. 142(2), 573 (2013)CrossRefGoogle Scholar
  8. 8.
    Li, J., Mohapatra, P.: Analytical modeling and mitigation techniques for the energy hole problem in sensor networks. Pervasive Mob. Comput. 3(3), 233–254 (2007)CrossRefGoogle Scholar
  9. 9.
    Li, Z., Peng, Y., Zhang, W., Qiao, D.: Study of joint routing and wireless charging strategies in sensor networks. In: Pandurangan, G., Anil Kumar, V.S., Ming, G., Liu, Y., Li, Y. (eds.) WASA 2010. LNCS, vol. 6221, pp. 125–135. Springer, Heidelberg (2010). Scholar
  10. 10.
    Maschler, M., Solan, E., Zamir, S.: Game Theory. Cambridge University Press, Cambridge (2013). Scholar
  11. 11.
    Myerson, R.B.: Graphs and cooperation in games. Math. Oper. Res. 2(3), 225–229 (1977)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Sedgwick, P.: Pearson’s correlation coefficient. BMJ 345, e4483 (2012)CrossRefGoogle Scholar
  13. 13.
    Shah, R.C., Roy, S., Jain, S., Brunette, W.: Data mules: modeling and analysis of a three-tier architecture for sparse sensor networks. Ad Hoc Netw. 1(2–3), 215–233 (2003)CrossRefGoogle Scholar
  14. 14.
    Shapley, L.S.: A value for n-person games. Contrib. Theory Games 2(28), 307–317 (1953)MathSciNetzbMATHGoogle Scholar
  15. 15.
    Shi, H.Y., Wang, W.L., Kwok, N.M., Chen, S.Y.: Game theory for wireless sensor networks: a survey. Sensors 12(7), 9055–9097 (2012)CrossRefGoogle Scholar
  16. 16.
    Skibski, O., Michalak, T.P., Rahwan, T., Wooldridge, M.: Algorithms for the Shapley and Myerson values in graph-restricted games. In: Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems, pp. 197–204. International Foundation for Autonomous Agents and Multiagent Systems (2014)Google Scholar
  17. 17.
    Solan, E., Vieille, N.: Quitting games. Math. Oper. Res. 26(2), 265–285 (2001)MathSciNetCrossRefGoogle Scholar
  18. 18.
    Solan, E., Vieille, N.: Quitting games-an example. Int. J. Game Theory 31(3), 365–381 (2003)MathSciNetCrossRefGoogle Scholar
  19. 19.
    Vecchio, M., Viana, A.C., Ziviani, A., Friedman, R.: DEEP: density-based proactive data dissemination protocol for wireless sensor networks with uncontrolled sink mobility. Comput. Commun. 33(8), 929–939 (2010)CrossRefGoogle Scholar
  20. 20.
    Ye, F., Luo, H., Cheng, J., Lu, S., Zhang, L.: A two-tier data dissemination model for large-scale wireless sensor networks. In: Proceedings of the 8th Annual International Conference on Mobile Computing and Networking, pp. 148–159. ACM (2002)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computing ScienceUniversity of AberdeenAberdeenScotland
  2. 2.Department of PhysicsUniversity of AberdeenAberdeenScotland

Personalised recommendations