Combining Cognitive with Computational Trust Reasoning

  • Eugen Staab
  • Thomas Engel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5396)


We propose a concept that combines the cognitive with the computational approaches to experience-based trust reasoning. We emphasize that a cognitive component is vital for computationally modeling trust. At the same time, we recognize the predictive nature of trust. This suggests a combination of the different approaches. The idea is to introduce a cognitive component that produces factual positive and factual negative experiences. These experiences can then be used in a predictive component to estimate the future behavior of an agent. The components are combined in a modular way which allows the replacement of them independently. It further facilitates the integration of already existing trust update algorithms. In this work, we analyze the chain of trust processing for the concept step by step. This results in a concise survey on challenges for experience-based trust models.


IEEE Computer Society Multiagent System Autonomous Agent Trust Management Proactive Behavior 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Castelfranchi, C., Falcone, R.: Principles of trust for MAS: Cognitive anatomy, social importance, and quantification. In: ICMAS 1998: Proc. of the 3rd Int. Conference on Multi-Agent Systems, pp. 72–79. IEEE Computer Society, Los Alamitos (1998)Google Scholar
  2. 2.
    Castelfranchi, C., Falcone, R.: Trust is much more than subjective probability: Mental components and sources of trust. In: HICSS 2000: Proc. of the 33rd Hawaii Int. Conf. on System Sciences. IEEE Computer Society, Los Alamitos (2000)Google Scholar
  3. 3.
    Falcone, R., Castelfranchi, C.: Social trust: a cognitive approach. Trust and deception in virtual societies, 55–90 (2001)Google Scholar
  4. 4.
    Wang, Y., Singh, M.P.: Formal trust model for multiagent systems. In: IJCAI 2007: Proc. of the 20th Int. Joint Conf. on Artificial Intelligence, pp. 1551–1556 (2007)Google Scholar
  5. 5.
    Capra, L., Musolesi, M.: Autonomic trust prediction for pervasive systems. In: AINA 2006: Proc. of the 20th Int. Conf. on Advanced Information Networking and Applications, vol. 2, pp. 481–488. IEEE Computer Society, Los Alamitos (2006)Google Scholar
  6. 6.
    Esfandiari, B., Chandrasekharan, S.: On how agents make friends: Mechanisms for trust acquisition. In: Proc. of the 4th Workshop on Deception, Fraud and Trust in Agent Societies (at AAMAS 2001), pp. 27–34 (2001)Google Scholar
  7. 7.
    Teacy, W.T.L., Patel, J., Jennings, N.R., Luck, M.: Travos: Trust and reputation in the context of inaccurate information sources. Auton. Agents Multi-Agent Syst. 12(2), 183–198 (2006)CrossRefGoogle Scholar
  8. 8.
    Witkowski, M., Pitt, J.: Objective trust-based agents: Trust and trustworthiness in a Multi-Agent trading society. In: ICMAS 2000: Proc. of the 4th Int. Conf. on Multi-Agent Systems, pp. 463–464. IEEE Computer Society, Los Alamitos (2000)Google Scholar
  9. 9.
    Zacharia, G.: Collaborative reputation mechanisms for online communities. Master’s thesis, Massachusetts Institute of Technology (1999)Google Scholar
  10. 10.
    Sabater, J., Sierra, C.: REGRET: Reputation in gregarious societies. In: Proc. of the 4th Workshop on Deception, Fraud and Trust in Agent Societies, pp. 194–195. ACM Press, New York (2001)Google Scholar
  11. 11.
    Huynh, T.D., Jennings, N.R., Shadbolt, N.R.: An integrated trust and reputation model for open multi-agent systems. Auton. Agents Multi-Agent Syst. 13(2), 119–154 (2006)CrossRefGoogle Scholar
  12. 12.
    Haas, Z.J., Deng, J., Liang, B., Papadimitratos, P., Sajama, S.: Wireless ad hoc networks. In: Perkins, C.E. (ed.) Ad Hoc Networking, pp. 221–225. Addison-Wesley, Reading (2001)Google Scholar
  13. 13.
    Şensoy, M., Yolum, P.: Ontology-based service representation and selection. IEEE Trans. Knowl. Data Eng. 19(8), 1102–1115 (2007)CrossRefGoogle Scholar
  14. 14.
    Marilly, E., Martinot, O., Betgé-Brezetz, S., Delègue, G.: Requirements for service level agreement management. In: IPOM 2002: Proc. of the IEEE Workshop on IP Operations and Management, pp. 57–62 (2002)Google Scholar
  15. 15.
    Falcone, R., Castelfranchi, C.: Trust dynamics: How trust is influenced by direct experiences and by trust itself. In: Kudenko, D., Kazakov, D., Alonso, E. (eds.) AAMAS 2004. LNCS, vol. 3394, pp. 740–747. Springer, Heidelberg (2005)Google Scholar
  16. 16.
    Mao, W., Gratch, J.: A utility-based approach to intention recognition. In: Kudenko, D., Kazakov, D., Alonso, E. (eds.) AAMAS 2004. LNCS, vol. 3394, Springer, Heidelberg (2005)Google Scholar
  17. 17.
    Demolombe, R., Fernandez, A.M.O.: Intention recognition in the situation calculus and probability theory frameworks. In: Toni, F., Torroni, P. (eds.) CLIMA 2005. LNCS, vol. 3900, pp. 358–372. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  18. 18.
    Staab, E., Engel, T.: Formalizing excusableness of failures in multi-agent systems. In: PRIMA 2007: Proc. of the 10th Pacific Rim Int. Workshop on Multi-Agents, pp. 124–135 (2007)Google Scholar
  19. 19.
    Mao, W., Gratch, J.: The social credit assignment problem. In: Rist, T., Aylett, R.S., Ballin, D., Rickel, J. (eds.) IVA 2003. LNCS, vol. 2792, pp. 39–47. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  20. 20.
    Weiner, B.: The Judgment of Responsibility. Guilford Press, New York (1995)Google Scholar
  21. 21.
    Lambert, D.M., Cooper, M.C.: Issues in supply chain management. Industrial Marketing Management 29, 65–83 (2000)CrossRefGoogle Scholar
  22. 22.
    Pearl, J.: Causality: models, reasoning, and inference. Cambridge University Press, Cambridge (2000)zbMATHGoogle Scholar
  23. 23.
    Staab, E., Fusenig, V., Engel, T.: Using correlation for collusion detection in grid settings. Technical Report 000657499, University of Luxembourg (July 2008)Google Scholar
  24. 24.
    Staab, E., Fusenig, V., Engel, T.: Towards trust-based acquisition of unverifiable information. In: Klusch, M., Pěchouček, M., Polleres, A. (eds.) CIA 2008. LNCS, vol. 5180, pp. 41–54. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  25. 25.
    Rehák, M., Pechoucek, M.: Trust modeling with context representation and generalized identities. In: Klusch, M., Hindriks, K.V., Papazoglou, M.P., Sterling, L. (eds.) CIA 2007. LNCS, vol. 4676, pp. 298–312. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  26. 26.
    Stefano, A.D., Terrazzino, G., Scalia, L., Tinnirello, I., Bianchi, G., Giaconia, C.: An experimental testbed and methodology for characterizing IEEE 802.11 network cards. In: WoWMoM 2006: Proc. of the 2006 International Symposium on a World of Wireless, Mobile and Multimedia Networks, pp. 513–518. IEEE Computer Society, Los Alamitos (2006)CrossRefGoogle Scholar
  27. 27.
    Sipser, M.: Introduction to the Theory of Computation. Int. Thomson Publishing (1996)Google Scholar
  28. 28.
    Grandison, T., Sloman, M.: Trust management tools for internet applications. In: iTrust 2003: Proc. of the 1st Int. Conf. on Trust Management, pp. 91–107. Springer, Heidelberg (2003)Google Scholar
  29. 29.
    Kinateder, M., Baschny, E., Rothermel, K.: Towards a generic trust model - comparison of various trust update algorithms. In: iTrust 2005: Proc. of the 3rd Int. Conf. on Trust Management, pp. 177–192. Springer, Heidelberg (2005)Google Scholar
  30. 30.
    McKnight, D.H., Chervany, N.L.: The meanings of trust. Technical report, University of Minnesota (1996)Google Scholar
  31. 31.
    Bradach, J.L., Eccles, R.G.: Price, authority, and trust: From ideal types to plural forms. Annu. Rev. Sociol. 15, 97–118 (1989)CrossRefGoogle Scholar
  32. 32.
    Dearden, R., Friedman, N., Andre, D.: Model based bayesian exploration. In: UAI 1999: Proc. of the 15th Conf. on Uncertainty in Artificial Intelligence, pp. 150–159 (1999)Google Scholar
  33. 33.
    Chalkiadakis, G., Boutilier, C.: Coordination in multiagent reinforcement learning: a bayesian approach. In: AAMAS 2003: Proc. of the 2nd Int. Joint Conf. on Autonomous Agents and Multiagent Systems, pp. 709–716. ACM, New York (2003)Google Scholar
  34. 34.
    Teacy, W.T.L., Chalkiadakis, G., Rogers, A., Jennings, N.R.: Sequential decision making with untrustworthy service providers. In: AAMAS 2008: Proc. of the 7th Int. Conf. on Autonomous Agents and Multiagent Systems, pp. 755–762 (2008)Google Scholar
  35. 35.
    Reches, S., Hendrix, P., Kraus, S., Grosz, B.J.: Efficiently determining the appropriate mix of personal interaction and reputation information in partner choice. In: AAMAS 2008: Proc. of 7th Int. Conf. on Autonomous Agents and Multiagent Systems, pp. 583–590 (2008)Google Scholar
  36. 36.
    Abdul-Rahman, A., Hailes, S.: Supporting trust in virtual communities. In: HICSS 2000: Proc. of the 33rd Hawaii Int. Conf. on System Sciences. IEEE Computer Society, Los Alamitos (2000)Google Scholar
  37. 37.
    Whitby, A., Jøsang, A., Indulska, J.: Filtering out unfair ratings in bayesian reputation systems. In: Kudenko, D., Kazakov, D., Alonso, E. (eds.) AAMAS 2004. LNCS, vol. 3394. Springer, Heidelberg (2005)Google Scholar
  38. 38.
    Sabater, J., Sierra, C.: Reputation and social network analysis in multi-agent systems. In: AAMAS 2002: Proc. of the 1st Int. Joint Conf. on Autonomous agents and multiagent systems, pp. 475–482. ACM, New York (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Eugen Staab
    • 1
  • Thomas Engel
    • 1
  1. 1.Faculty of Science, Technology and CommunicationUniversity of LuxembourgLuxembourg

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