Advertisement

Budget Limited Trust-Aware Decision Making

  • Taha D. Güneş
  • Timothy J. Norman
  • Long Tran-Thanh
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10643)

Abstract

Utilizing witness information to supplement direct evidence is commonly used to build assessments of the trustworthiness of agents. The process of acquiring this kind of evidence is, however, typically assumed to be cost-free. In practice, agents are budget-limited, and investments in acquiring witness (or reputation) information will affect the budget that can be used for direct interaction. At the same time, acquiring such witness information can help in making better trust decisions. We explore this trade-off, formalising it as a budget-limited multi-armed bandit problem, and evaluate the effectiveness of algorithms to guide this decision process.

References

  1. 1.
    Yu, H., Miao, C., An, B., Leung, C., Lesser, V.: A reputation management approach for resource constrained trustee agents. In: International Joint Conference on Artificial Intelligence (2013)Google Scholar
  2. 2.
    Jøsang, A., Ismail, R.: The beta reputation system. In: Proceedings of the 15th Bled Electronic Commerce Conference, vol. 5, pp. 2502–2511 (2002)Google Scholar
  3. 3.
    Regan, K., Poupart, P., Cohen, R.: Bayesian reputation modeling in e-marketplaces sensitive to subjectivity, deception and change. In: Proceedings of the National Conference on Artificial Intelligence, vol. 21, p. 1206 (2006)Google Scholar
  4. 4.
    Teacy, W.L., Luck, M., Rogers, A., Jennings, N.R.: An efficient and versatile approach to trust and reputation using hierarchical Bayesian modelling. Artif. Intell. 193, 149–185 (2012)MathSciNetCrossRefzbMATHGoogle Scholar
  5. 5.
    Jøsang, A., Ismail, R., Boyd, C.: A survey of trust and reputation systems for online service provision. Decis. Support Syst. 43(2), 618–644 (2007)CrossRefGoogle Scholar
  6. 6.
    Sen, S., Ridgway, A., Ripley, M.: Adaptive budgeted bandit algorithms for trust in a supply-chain setting. In: Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, pp. 137–144 (2015)Google Scholar
  7. 7.
    Tran-Thanh, L.: Budget-limited multi-armed bandits. Ph.D. thesis, University of Southampton (2012)Google Scholar
  8. 8.
    Etuk, A., Norman, T.J., Şensoy, M., Srivatsa, M.: How to trust a few among many. Auton. Agents Multi-agent Syst. 31(3), 531–560 (2016)CrossRefGoogle Scholar
  9. 9.
    Jøsang, A., Hayward, R., Pope, S.: Trust network analysis with subjective logic. In: Proceedings of the 29th Australasian Computer Science Conference, pp. 85–94 (2006)Google Scholar
  10. 10.
    Stein, W.E., Seale, D.A., Rapoport, A.: Analysis of heuristic solutions to the best choice problem. Eur. J. Oper. Res. 151(1), 140–152 (2003)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Wang, D., Muller, T., Liu, Y., Zhang, J.: Towards robust and effective trust management for security: a survey. In: Proceedings of the 13th International Conference on Trust, Security and Privacy in Computing and Communications, pp. 511–518 (2014)Google Scholar
  12. 12.
    Wang, Y., Singh, M.P.: Formal trust model for multiagent systems. In: Proceedings of the 20th International Joint Conference on Artifical Intelligence, pp. 1551–1556 (2007)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Agents, Interaction and Complexity GroupUniversity of SouthamptonSouthamptonUK

Personalised recommendations