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Agent Argumentation with Opinions and Advice

  • John Debenham
  • Carles Sierra
Conference paper

Abstract

In argumentation-based negotiation the rhetorical illocutionary particles Appeals, Rewards and Threats have implications for the players that extend beyond a single negotiation and are concerned with building (business) relationships. This paper extends an agent’s relationship-building argumentative repertoire with Opinions and Advice. A framework is described that enables agents to model their relationships and to use argumentative dialogue strategically both to achieve good negotiation outcomes and to build and sustain valuable relationships.

Keywords

Semantic Similarity Information Gain World Model Relationship Model Epistemic Belief 
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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References

  1. 1.
    FIPA Communicative Act Library Specification. Tech. Rep. SC00037J, Foundation for Intelligent Physical Agents, Geneva, Switzerland (2002)Google Scholar
  2. 2.
    Adams, J.S.: Inequity in social exchange. In: L. Berkowitz (ed.) Advances in experimental social psychology, vol. 2. New York: Academic Press (1965)Google Scholar
  3. 3.
    Artz, D., Gil, Y.: A survey of trust in computer science and the semantic web. Web Semantics: Science, Services and Agents on the World Wide Web 5(2), 58–71 (2007)CrossRefGoogle Scholar
  4. 4.
    Bazerman, M.H., Loewenstein, G.F., White, S.B.: Reversal of preference in allocation decisions: judging an alternative versus choosing among alternatives. Administration Science Quarterly (37), 220–240 (1992)Google Scholar
  5. 5.
    Cheeseman, P., Stutz, J.: Bayesian Inference and Maximum Entropy Methods in Science and Engineering, chap. On The Relationship between Bayesian and Maximum Entropy Inference, pp. 445 – 461. American Institute of Physics, Melville, NY, USA (2004)Google Scholar
  6. 6.
    Faratin, P., Sierra, C., Jennings, N.: Using similarity criteria to make issue trade-offs in automated negotiation. Journal of Artificial Intelligence 142(2), 205–237 (2003)CrossRefMathSciNetGoogle Scholar
  7. 7.
    Grünwald, P.D.: The Minimum Description Length Principle. MIT Press, Cambridge, MA (2007)Google Scholar
  8. 8.
    Kalfoglou, Y., Schorlemmer, M.: IF-Map: An ontology-mapping method based on information-flow theory. In: S. Spaccapietra, S. March, K. Aberer (eds.) Journal on Data Semantics I, Lecture Notes in Computer Science, vol. 2800, pp. 98–127. Springer-Verlag: Heidelberg, Germany (2003)Google Scholar
  9. 9.
    Li, Y., Bandar, Z.A., McLean, D.: An approach for measuring semantic similarity between words using multiple information sources. IEEE Transactions on Knowledge and Data Engineering 15(4), 871–882 (2003)CrossRefGoogle Scholar
  10. 10.
    Paris, J.: Common sense and maximum entropy. Synthese 117(1), 75–93 (1999)CrossRefMathSciNetGoogle Scholar
  11. 11.
    Rahwan, I., Ramchurn, S., Jennings, N., McBurney, P., Parsons, S., Sonenberg, E.: Argumentation-based negotiation. Knowledge Engineering Review 18(4), 343–375 (2003)CrossRefGoogle Scholar
  12. 12.
    Rauyruena, P., Miller, K.E.: Relationship quality as a predictor of B2B customer loyalty. Journal of Business Research 60(1), 21–31 (2007)CrossRefGoogle Scholar
  13. 13.
    Sabater, J., Sierra, C.: Review on computational trust and reputation models. Artificial Intelligence Review 24(1), 33–60 (2005)MATHCrossRefGoogle Scholar
  14. 14.
    Sierra, C., Debenham, J.: Trust and honour in information-based agency. In: P. Stone, G.Weiss (eds.) Proceedings Fifth International Conference on Autonomous Agents and Multi Agent Systems AAMAS-2006, pp. 1225–1232. ACM Press, New York, Hakodate, Japan (2006)CrossRefGoogle Scholar
  15. 15.
    Sierra, C., Debenham, J.: Information-based agency. In: Proceedings of Twentieth International Joint Conference on Artificial Intelligence IJCAI-07, pp. 1513–1518. Hyderabad, India (2007)Google Scholar
  16. 16.
    Sierra, C., Debenham, J.: The LOGIC Negotiation Model. In: Proceedings Sixth International Conference on Autonomous Agents and Multi Agent Systems AAMAS-2007, pp. 1026–1033. Honolulu, Hawai’i (2007)Google Scholar
  17. 17.
    Sierra, C., Jennings, N., Noriega, P., Parsons, S.: Proceedings of the 4th International Workshop on Intelligent Agents IV, Agent Theories, Architectures, and Languages, chap. A Framework for Argumentation-Based Negotiation, pp. 177 – 192. Springer-Verlag, London, UK (1997)Google Scholar
  18. 18.
    Suzuki, J.: Learning bayesian belief networks based on the MDL principle: An efficient algorithm using the branch and bound technique. IEICE TRANSACTIONS on Information and Systems E81-D(12), 356–367 (1998)Google Scholar
  19. 19.
    Ulaga, W., Eggert, A.: Relationship value in business markets: The construct and its dimensions. Journal of Business To Business Marketing 12(1), 73–99 (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.QCIS, UTSBroadwayAustralia
  2. 2.IIIA, CSICBellaterraSpain

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