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Computational Trust and Reputation Models

Computational Trust and Reputation Models. Andrew Diniz da Costa andrew@les.inf.puc-rio.br. Presentation Outline. Part 1: Introduction Motivation Some definitions Part 2: Computational trust and reputation models eBay/OnSale SPORAS & HISTOS Fire Model Governance Framework

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Computational Trust and Reputation Models

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  1. Computational Trust andReputation Models Andrew Diniz da Costa andrew@les.inf.puc-rio.br

  2. Presentation Outline • Part 1: Introduction • Motivation • Some definitions • Part 2: Computational trust and reputation models • eBay/OnSale • SPORAS & HISTOS • Fire Model • Governance Framework • Part 3: ART-Testbed • Overview Andrew Diniz da Costa © LES/PUC-Rio

  3. Presentation Outline • Part 1: Introduction • Motivation • Some definitions • Part 2: Computational trust and reputation models • eBay/OnSale • SPORAS & HISTOS • Fire Model • Governance Framework • Part 3: ART-Testbed • Overview Andrew Diniz da Costa © LES/PUC-Rio

  4. What we are talking about ... Andrew Diniz da Costa © LES/PUC-Rio

  5. What we are talking about ... Andrew Diniz da Costa © LES/PUC-Rio

  6. Advantages of trust and reputation mechanisms • Agents can obtain data from others agents. • Shared experience. • Decide on which to trust Andrew Diniz da Costa © LES/PUC-Rio

  7. Problems of trust and reputation mechanisms • Not all kind of environments are suitable to apply these mechanisms. • Exclusion must be a punishment • What is trust? • What is reputation? Andrew Diniz da Costa © LES/PUC-Rio

  8. Trust • Some statements we like: • “Trust begins where knowledge ends: trust provides a basis dealing with uncertain, complex, and threatening images of the future.” [Luhmann,1979] • “There are no obvious units in which trust can be measured,” [Dasgupta, 2000] Andrew Diniz da Costa © LES/PUC-Rio

  9. Reputation • Some definitions: • “The estimation of the consistency over time of an attribute or entity” [Herbig et al.] • “Information that individuals receive about the behaviour of their partners from third parties and that they use to decide how to behave themselves” [Buskens, Coleman...] • “The opinion others have of us” Andrew Diniz da Costa © LES/PUC-Rio

  10. What is a good trust model? • A good trust model should be [Fullam et al, 05]: • Accurate • provide good previsions • Adaptive • evolve according to behaviour of others • Multi-dimensional • Consider different agent characteristics • Efficient • Compute in reasonable time and cost Andrew Diniz da Costa © LES/PUC-Rio

  11. Why using a trust model in a MAS ? • Trust models allow: • Identifying and isolating untrustworthy agents • Evaluating an interaction’s utility • Deciding whether and with whom to interact Andrew Diniz da Costa © LES/PUC-Rio

  12. Presentation Outline • Part 1: Introduction • Motivation • Some definitions • Part 2: Computational trust and reputation models • eBay/OnSale • SPORAS & HISTOS • Fire model • Governance Framework • Part 3: ART-Testbed • Overview Andrew Diniz da Costa © LES/PUC-Rio

  13. eBay model • Context: e-commerce • Model oriented to support trust between buyer and seller • Buyer has no physical access to the product of interest • Seller or buyer may decide not to commit the transaction • Centralized: all information remains on eBay Servers • Buyers and sellers evaluate each other after transactions • The evaluation is not mandatory and will never be removed • Each eBay member has a “reputation” (feedback score) that is the summation of the numerical evaluations. Andrew Diniz da Costa © LES/PUC-Rio

  14. eBay model Andrew Diniz da Costa © LES/PUC-Rio

  15. eBay model Andrew Diniz da Costa © LES/PUC-Rio

  16. SPORAS & HISTOS • Context: e-commerce, similar to eBay • An individual may have a very high reputation in one domain, while she has a low reputation in another. • Two models are proposed: • Sporas: works even with few evaluations (ratings) • Histos: assumes abundance of evaluations • Ratings given by users with a high reputation are weighted more • Reputation values are not allowed to increase at infinitum Andrew Diniz da Costa © LES/PUC-Rio

  17. SPORAS & HISTOS • SPORAS • Reputations are in [0, 3000]. Newcommers = 0. Ratings are in [0.1, 1] • Reputations never get below 0, even in the case of very bad behaviours • After each rating the reputation is updated • HISTOS • Aim: compute a global ‘personalized reputation’ value for each member Andrew Diniz da Costa © LES/PUC-Rio

  18. Fire Model • Three types of reputation • Interaction trust • Witness reputation • Certified reputation * Huynh, T. D., Jennings, N. R. and Shadbolt, N. (2004) FIRE: an integrated trust and reputation model for open multi-agent systems. In: 16th European Conference on Artificial Intelligence, 2004, Valencia, Spain. Andrew Diniz da Costa © LES/PUC-Rio

  19. Fire Model • Interaction trust • resulting from past experiences from direct interactions • Between [-1, +1] • -1 means absolutely negative • +1 means absolutely positive • 0 means neutral or uncertain Interaction Trust of the Agent B (price, quality, etc) Request Provide Agent B Agent A Andrew Diniz da Costa © LES/PUC-Rio

  20. Fire Model • Witness reputation • reports of witness about an agent’s behaviour Agent C knows Agent B Request witness Agent C Agent D knows Agent B Request witness Agent B Agent A Agent D Request witness Agent E knows Agent B Agent E Andrew Diniz da Costa © LES/PUC-Rio

  21. Fire Model • Certified reputation • references provided by other agents about its behaviour Evaluation of D made by the agent A Agent D Evaluation of A made by the agent D Evaluation of B made by the agent A 0,5 Agent A -0,5 Agent B What is your reputation Evaluation of A made by the agent B 0,5 Agent C Andrew Diniz da Costa © LES/PUC-Rio

  22. Governance Framework - GUEDES, José ; SILVA, V. T. ; LUCENA, Carlos José Pereira de . A Reputation Model Based on Testimonies. In: Kolp, M, Garcia, A, Ghoze, C, Bresciani, P, Henderson-Sellers, B, Mouratidis, M.. (Org.). Agent-Oriented Information Systems.: Springer-Verlag, 2008, v. LNAI, p. 37-52. - DURAN, Feranda ; SILVA, V. T. ; LUCENA, Carlos José Pereira de . Using Testimonies to Enforce the behavior of Agents. In: Sichman, J., Noriega, P., Padget, J. and Ossowski, S.. (Org.). Coordination, Organizations, Institutions and Norms in Agent Systems III. : Springer-Verlag, 2008, v. LNAI, p. 218-231. Andrew Diniz da Costa © LES/PUC-Rio

  23. Governance Framework – Reputation System • Three different kinds of reputations were defined: • role reputation,norm reputation and global reputation. • Role reputations only consider norms that were violated while playing a specified role or lies that were told while playing the role. • Norm reputations focus on the violation of a norm and on the lies told while considering a norm. • The global reputation of an agent considers all violated norms and all told lies. Andrew Diniz da Costa © LES/PUC-Rio

  24. Presentation Outline • Part 1: Introduction • Motivation • Some definitions • Part 2: Computational trust and reputation models • eBay/OnSale • SPORAS & HISTOS • Fire Model • Governance Framework • Part 3: ART-Testbed • Overview Andrew Diniz da Costa © LES/PUC-Rio

  25. Domain Andrew Diniz da Costa © LES/PUC-Rio

  26. Reputation Transaction Protocol Andrew Diniz da Costa © LES/PUC-Rio

  27. Opinion Transaction Protocol Andrew Diniz da Costa © LES/PUC-Rio

  28. Simulator Andrew Diniz da Costa © LES/PUC-Rio

  29. Competition • 17 agents (1 didn’t execute) of 13 different institutions • Two phases • Preliminary • Final • Preliminary phase (May 10-11) • 8 agents of the different institutions • 15 agents offered by competition (5 “bad”, 5 “neutral”, 5 “bad” dummies ) • 100 rounds • Final phase (May 16-17) • 5 best agents of the preliminary phase • 15 agents offered by competition (5 “bad”, 5 “neutral”, 5 “bad” dummies ) • 200 rounds Andrew Diniz da Costa © LES/PUC-Rio

  30. Preliminary Phase Andrew Diniz da Costa © LES/PUC-Rio

  31. Final Phase 1) Electronics & Computer Science, University of Southampton 2) Department of Math & Computer Science, The University of Tulsa 3) Department of Computer Engineering, Bogazici University 4) Agents Research Lab, University of Girona 5) Pontifícia Universidade Católica do Rio de Janeiro Andrew Diniz da Costa © LES/PUC-Rio

  32. Conclusion • ART-Testbed is being useful, however: • What is reputation? • Unreal Domain • Researches have worked in domains of the industry to apply trust and reputation. • Area is growing • Famous researches are working in this area. Andrew Diniz da Costa © LES/PUC-Rio

  33. References • [AbdulRahman, 97] A. Abdul-Rahman. The PGP trust model. EDI-Forum: the Journal of Electronic Commerce, 10(3):27–31, 1997. • [Barber, 83] B. Barber, The Logic and Limits of Trust, The meanings of trust: Technical competence and fiduciary responsibility, Rutgers University Press, Rutgers, NJ, United States of America, 1983, p. 7-25. • [Carbo et al., 03] J. Carbo and J. M. Molina and J. {Dávila Muro, Trust Management Through Fuzzy Reputation, International Journal of Cooperative Information Systems, 2003, vol. 12:1, p. 135-155. • [Casare & Sichman, 05] S. J. Casare and J. S. Sichman, Towards a functional ontology of reputation, Proceedings of AAMAS’05, 2005. • [Castelfranchi, 00] C. Castelfranchi, Engineering Social Order, Proceedings of ESAW’00, 2000. • [Castelfranchi & Falcone, 98] C. Castelfranchi and R. Falcone, Principles of trust for MAS: Cognitive anatomy, social importance and quantification. Proc of ICMAS’98, pages 72-79, 1998. • [Conte & Paolucci, 02] R. Conte and M. Paolucci, Reputation in Artificial Societies. Social Beliefs for Social Order, Kluwer Academic Publishers, G. Weiss (eds), Dordrecht, The Netherlands, 2002. • [Dellarocas, 00] C. Dellarocas, Immunizing online reputation reporting systems against unfair ratings and discriminatory behavior, p. 150-157, Proceedings of the ACM Conference on "Electronic Commerce“ (EC'00), October, ACM Press, New York, NY, United States of America, 2000. • [Dellarocas, 01] C. Dellarocas, Analyzing the economic efficiency of {eBay-like} online reputation reporting mechanisms, p. 171-179, Proceedings of the ACM Conference on "Electronic Commerce" (EC'01), October, ACM Press, New York, NY, United States of America, 2001. • [Demolombe & Lorini, 08] R. Demolombe and E. Lorini, Trust and norms in the context of computer security: a logical formalization. Proc of DEON’08, LNAI, 1998. Andrew Diniz da Costa © LES/PUC-Rio

  34. References • [Fullam et al, 05] K. Fullam, T. Klos, G. Muller, J. Sabater-Mir, A. Schlosser, Z. Topol, S. Barber, J. Rosenschein, L. Vercouter and M. Voss, A Specification of the Agent Reputation and Trust (ART) Testbed: Experimentation and Competition for Trust in Agent Societies, Proceedings of AAMAS’05, 2005. • [Herzig et al, 08] A. Herzig, E. Lorini, J. F. Hubner, J. Ben-Naim, C. Castelfranchi, R. Demolombe, D. Longin and L. Vercouyter. Prolegomena for a logic of trust and reputation, submitted to Normas 08. • [Luhmann, 79] N. Luhmann, Trust and Power, John Wiley \& Sons, 1979. [McKnight & Chervany, 02] D. H. McKnight and N. L. Chervany, What trust means in e-commerce customer relationship: an interdisciplinary conceptual typology, International Journal of Electronic Commerce, 2002. • [Mui et al., 02] L. Mui and M. Mohtashemi and A. Halberstadt, Notions of Reputation in Multi-agent Systems: A Review, Proceedings of Autonomous Agents and Multi-Agent Systems (AAMAS'02), p. 280-287, 2002, C. Castelfranchi and W.L. Johnson (eds), Bologna, Italy, July, ACM Press, New York, NY, United States of America. • [Muller & Vercouter, 05] G. Muller and L. Vercouter, Decentralized Monitoring of Agent Communication with a Reputation Model, Trusting Agents for trusting Electronic Societies, LNCS 3577, 2005. • [Pearl, 88] Pearl, J. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference, Morgan Kaufmann, San Francisco, 1988. • [Rehák et al., 05] M. Rehák and M. Pěchouček and P. Benda and L. Foltn, Trust in Coalition Environment: Fuzzy Number Approach, Proceedings of the Workshop on "Trust in Agent Societies" at Autonomous Agents and Multi-Agent Systems (AAMAS'05), p. 132-144, 2005, C. Castelfranchi and S. Barber and J. Sabater and M. P. Singh (eds) Utrecht, The Netherlands, July. • [Sabater, 04] Evaluating the ReGreT system Applied Artificial Intelligence, 18 (9-10) :797-813. • [Sabater & Sierra, 05] Review on computational trust and reputation models Artificial Intelligence Review ,24 (1) :33-60. Andrew Diniz da Costa © LES/PUC-Rio

  35. References • [Sabater-Mir & Paolucci, 06] Repage: REPutation and imAGE among limited autonomous partners, JASSS - Journal of Artificial Societies and Social Simulation ,9 (2), 2006. • [Schillo & Funk, 99] M. Schillo and P. Funk, Learning from and about other agents in terms of social metaphors, Agents Learning About From and With Other Agents, 1999. • [Sen & Sajja, 02] S. Sen and N. Sajja, Robustness of reputation-based trust: Boolean case, Proceedings of Autonomous Agents and Multi-Agent Systems (AAMAS'02), p. 288-293, 2002, Bologna, Italy, M. Gini and T. Ishida and C. Castelfranchi and W. L. Johnson (eds), ACM Press, New York, NY, United States of America, vol.1. • [Shapiro, 87] S. P. Shapiro, The social control of impersonal trust, American Journal of Sociology, 1987, vol. 93, p. 623-658. • [Steiner, 03] D. Steiner, Survey: How do Users Feel About eBay's Feedback System? January, 2003, http://www.auctionbytes.com/cab/abu/y203/m01/abu0087/s02 . • [Zacharia et al., 99] G. Zacharia and A. Moukas and P. Maes, Collaborative Reputation Mechanisms in Electronic Marketplaces, Proceedings of the Hawaii International Conference on System Sciences (HICSS-32), vol. 08, 1999, p. 8026, IEEE Computer Society, Washington, DC, United States of America. Andrew Diniz da Costa © LES/PUC-Rio

  36. Perguntas... Andrew Diniz da Costa andrew@les.inf.puc-rio.br Andrew Diniz da Costa © LES/PUC-Rio

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