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Protecting buying agents in e-marketplaces by direct experience trust modelling

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Abstract

In this paper, we describe a framework for modelling the trustworthiness of sellers in the context of an electronic marketplace where multiple selling agents may offer the same good with different qualities and selling agents may alter the quality of their goods. We consider that there may be dishonest sellers in the market (for example, agents who offer goods with high quality and later offer the same goods with very low quality). In our approach, buying agents use a combination of reinforcement learning and trust modelling to enhance their knowledge about selling agents and hence their opportunities to purchase high value goods in the marketplace. This paper focuses on presenting the theoretical results demonstrating how the modelling of trust can protect buying agents from dishonest selling agents. The results show that our proposed buying agents will not be harmed infinitely by dishonest selling agents and therefore will not incur infinite loss, if they are cautious in setting their penalty factor. We also discuss the value of our particular model for trust, in contrast with related work and conclude with directions for future research.

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References

  1. Bakos Y, Dellarocas C (2003) Cooperation without enforcement? A comparative analysis of litigation and online reputation as quality assurance mechanisms. In: MIT Sloan School of Management, Working Paper 4295-03

  2. Barber KS, Kim J (2002) Soft security: isolating unreliable agents from society. In: Proceedings of the First International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-02) Workshop on Trust, Reputation and Security: Theories and Practice

  3. Breban S, Vassileva J (2002) Using inter-agent trust relationships for efficient coalition formation. In: Proceedings of the Fifteenth Conference of the Canadian Society for Computational Studies of Intelligence, pp 221–236

  4. Carter J, Ghorbani A, Marsh S (2002) Architectural components of information-sharing societies. Comput Intell Spec Issue Agent Technol Electron Commer 18(4): 638–655

    MathSciNet  Google Scholar 

  5. Chavez A, Maes P (1996) Kasbah: an agent marketplace for buying and selling goods. In: Proceedings of the First International Conference on the Practical Application of Intelligent Agents and Multi-Agent Technology

  6. Chiang H, Liao Y (2004) An agent-based framework for impulse-induced mobile shopping. In: Proceedings of the Fourth International Conference on Computer and Information Technology, pp 509–514

  7. Davis R, Smith RG (1983) Negotiation as a metaphor for distributed problem solving. Artif Intell 20(1): 63–109

    Article  Google Scholar 

  8. Rosis F, Carofiglio V, Grassano G, Castelfranchi C (2003) Can computers deliberately deceive? A simulation tool and its application to turing’s imitation game. Comput Intell 19(3): 235–263

    Article  Google Scholar 

  9. Esfandiari B, Chandrasekharan S (2001) On how agents make friends: mechanisms for trust acquisition. In: Proceedings of the Fifth International Conference on Autonomous Agents Workshop on Deception, Fraud and Trust in Agent Societies, pp 27–34

  10. Fullam KK, Barber KS (2007) Dymanically learning sources of trust information: experience vs. reputation. In: Proceedings of the Sixth International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-07)

  11. Huynh TD, Jennings NR, Shadbolt NR (2006) An integrated trust and reputation model for open multi-agent systems. J Auton Agent Multi Agent Syst 13: 119–154

    Article  Google Scholar 

  12. Jones S, Marsh S (1997) Human–computer–human interaction: trust in CSCW. SIGCHI 29(3)

  13. Jonker C, Treur J (1999) Formal analysis of models for the dynamics of trust based on experiences. In: Proceedings of the Fourth International Conference on Autonomous Agents Workshop on Deception, Fraud and Trust in Agent Societies, pp 81–94

  14. Jurca R, Faltings B (2003) An incentive-compatible reputation mechanism. In: Proceedings of the IEEE Conference on E-Commerce

  15. Jurca R, Faltings B (2002) Towards incentive-compatible reputation management. In: Proceedings of the First International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-02) Workshop on Deception, Fraud and Trust in Agent Societies

  16. Keegan S, O’Hare G M P (2004) Easishop: delivering cross merchant product comparison shopping for the mobile user. In: Proceedings of the Fifteenth IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC-04), pp 1860–1864

  17. Kerr R, Cohen R (2007) Towards provably secure trust and reputation systems in e-marketplaces. In: Proceedings of the Sixth International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-07)

  18. Kerr R, Cohen R (2006) Modeling trust using transactional, numerical units. In: Proceedings of the Conference on Privacy, Security and Trust (PST-06)

  19. Regan K, Tran T, Cohen R (2005) Sharing models of sellers amongst buying agents in electronic marketplaces. In: Proceedings of the 10th International Conference on User Modeling (UM-05) Workshop on Decentralized, Agent Based and Social Approaches to User Modelling

  20. Leung CW, Chan SC, Chung F (2006) A collaborative filtering framework based on fuzzy association rules and multiple-level similarity. Knowl Inform Syst 10(3): 357–381

    Article  Google Scholar 

  21. Rosendahl A, Hampe J F, Botterweck G (2007) Mobile home automation—merging mobile value added services and home automation technologies. In: Proceedings of the Sixth International Conference on Mobile Business (ICMB-07)

  22. Russell S, Norvig P (1995) Artificial intelligence: a modern approach. Prentice Hall, Englewood Cliffs

    MATH  Google Scholar 

  23. Sabater J, Sierra C (2001) REGRET: a reputation model for gregarious societies. In: Proceedings of the Fifth International Conference on Autonomous Agents Workshop on Deception, Fraud and Trust in Agent Societies, pp 61–69

  24. Sen S, Sekaran M, Hale J (1994) Learning to coordinate without sharing information. In: Proceedings of the Twelfth National Conference on Artificial Intelligence, pp 426–431

  25. Smith RG (1980) The contract net protocol: high level communication and control in a distributed problem solver. IEEE Trans Comput C-29(12): 1104–1113

    Article  Google Scholar 

  26. Sutton R, Barto A (1998) Reinforcement learning: an introduction. MIT Press, Cambridge

    Google Scholar 

  27. Teacy WTL, Patel J, Jennings NR, Luck M (2005) Coping with inaccurate reputation sources: experimental analysis of a probabilistic trust model. In: Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems

  28. Tran T, Cohen R (2004a) Improving user satisfaction in agent-based electronic marketplaces by reputation modelling and adjustable product quality. In: Proceedings of the Third International Joint Conference on Autonomous Agents and Multi Agent Systems (AAMAS-04), vol 2, pp 828–835

  29. Tran T, Cohen R (2004b) The advantages of designing adaptive business agents using reputation modelling compared to the approach of recursive modelling. Comput Intell Spec Issue Bus Agents Semant Web 20(4): 532–547

    MathSciNet  Google Scholar 

  30. Vidal JM, Durfee EH (1996) The impact of nested agent models in an information economy. In: Proceedings of the Second International Conference on Multi-Agent Systems, pp 377–384

  31. Weng Z, Tran T (2007) A mobile intelligent agent-based architecture for e-business. Int J Inform Technol Web Eng 2(4): 63–80

    Google Scholar 

  32. Wong T, Lam W (2008) Learning to extract and summarize hot item features from multiple auction web sites. Knowl Inform Syst 14(2): 143–160

    Article  Google Scholar 

  33. Yu B, Singh MP (2000) A social mechanism of reputation management in electronic communities. In: Klusch M, Kerschberg L (eds) Cooperative information agents IV, Lecture Notes in Artificial Intelligence, vol. 1860. Springer, Berlin, pp 154–165

    Google Scholar 

  34. Zhang J, Cohen R (2007a) An incentive mechanism for eliciting fair ratings of sellers in e-marketplaces. In: Proceedings of the Sixth International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-07)

  35. Zhang J, Cohen R (2007b) Design of a mechanism for promoting honesty in e-marketplaces. In: Proceedings of the Twenty Second National Conference on Artificial Intelligence (AAAI-07)

  36. Zhang J, Cohen R (2007c) Evaluating the trustworthiness of advice about selling agents in e-marketplaces: a personalized approach. Electronic Commerce Research and Applications

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  1. School of Information Technology and Engineering, University of Ottawa, 800 King Edward Avenue, Ottawa, ON, Canada, K1N 6N5

    Thomas Tran

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  1. Thomas Tran
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Correspondence to Thomas Tran.

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Tran, T. Protecting buying agents in e-marketplaces by direct experience trust modelling. Knowl Inf Syst 22, 65–100 (2010). https://doi.org/10.1007/s10115-008-0188-5

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  • DOI: https://doi.org/10.1007/s10115-008-0188-5

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