Skip to main content

Constructing the Structure of Utility Graphs Used in Multi-Item Negotiation Through Collaborative Filtering of Aggregate Buyer Preferences

  • Chapter
Rational, Robust, and Secure Negotiations in Multi-Agent Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 89))

Negotiation represents a key form of interaction between providers and consumers in electronic markets. One of the main benefits of negotiation in e-commerce is that it enables greater customization to individual customer preferences, and it supports buyer decisions in settings which require agreements over complex contracts. Automating the negotiation process, through the use of intelligent agents which negotiate on behalf of their owners, enables electronic merchants to go beyond price competition by providing flexible contracts, tailored to the needs of individual buyers.

Multi-issue (or multi-item) negotiation models are particularly useful for this task, since with multi-issue negotiations mutually beneficial (“win-win”) contracts can be found [7, 9, 12, 13, 20]. In this chapter we consider the negotiation over the contents of a bundle of items (thus we use the term “multi-item” negotiation), though, at a conceptual level, the setting is virtually identical to previous work on multi-issue negotiation involving only binary-valued issues (e.g. [13]). A bottleneck in most existing approaches to automated negotiation is that they only deal with linearly additive utility functions, and do not consider high-dimensional negotiations and in particular, the problem of inter-dependencies between evaluations for different items. This is a significant problem, since identifying and exploiting substitutability/ complementarity effects between different items can be crucial in reaching mutually profitable deals.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Boutilier, C., Patrascu, R.P.P., Schuurmans, D.: Regret-based utility elicitation in constraint-based decision problems. In: Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence (IJCAI-05). (2005) 929–934

    Google Scholar 

  2. Brazunias, D., Boutilier, C.: Local utility elicitation in gai models. In: Proceedings of the Twenty-first Conference on Uncertainty in Artificial Intelligence (UAI-05). (2005) 42–49

    Google Scholar 

  3. Chajewska, U., Koller, D.: Utilities as random variables: Density estimation and structure discovery. In: Proceedings of sixteenth Annual Conference on Uncertainty in Artificial Intelligence UAI-00. (2000) 63–71

    Google Scholar 

  4. Conitzer, V., Sandholm, T., Santi, P.: Combinatorial auctions with k-wise dependent valuations. In: Proceedings of the National Conference on Artificial Intelligence (AAAI). (2005)

    Google Scholar 

  5. Debenham, J.K.: Bargaining with information. In: Third International Conference on Autonomous Agents and Multi Agent Systems (AAMAS). (2004) 663–670

    Google Scholar 

  6. Dechter, R.: Constraint Processing. Morgan Kaufmann, Los Altos, CA (2003)

    Google Scholar 

  7. Faratin, P., Sierra, C., Jennings., N.R.: Using similarity criteria to make issue trade-offs in automated negotiations. Journal of Artificial Intelligence 142(2) (2002) 205–237

    Article  MathSciNet  Google Scholar 

  8. Fatima, S., Woolridge, M.N.J.: Optimal negotiation of multiple issues in incomplete information settings. In: Third International Conference on Autonomous Agents and Multi Agent Systems (AAMAS). (2004) 1080–1087

    Google Scholar 

  9. Gerding, E., Somefun, D., Poutré, La Poutré, J.A.: Multi-attribute bilateral bargaining in a one-to-many setting. In: Proceedings of the AMEC VI Workshop. (2004)

    Google Scholar 

  10. Guttman, R., Maes, P.: Agent-mediated integrative negotiation for retail electronic commerce. In: Agent Mediated Electronic Commerce, Springer LNAI 1571 (1998) 70–90

    Google Scholar 

  11. Janson, S., Luczak, T.A.R.: Random Graphs. Wiley, New York (2000)

    MATH  Google Scholar 

  12. Jennings, N.R., Coehoorn, R.M.: Learning an opponent’s preferences to make effective multi-issue negotiation tradeoffs. In: Proceedings of the Sixth International Conference on E-Commerce. (2004)

    Google Scholar 

  13. Klein, M., Faratin, P., Sayama, H., Bar-Yam, Y.: Negotiating complex contracts. Group Decision and Negotiation 12 (2003) 111–125

    Article  Google Scholar 

  14. Lin, R.: Bilateral multi-issue contract negotiation for task redistribution using a mediation service. In: Proceedings of the Agent Mediated Electronic Commerce VI. (2004)

    Google Scholar 

  15. Luo, X., Jennings, N.R., Shadbolt, N., Leung, H., Lee, J.H.: A fuzzy constraint based model for bilateral multi-issue negotiations in semi-competitive environments. Artificial Intelligence Journal 142 (1–2) (2003) 53–102

    Article  MathSciNet  Google Scholar 

  16. Raiffa, H.: The Art and Science of Negotiation. Harvard University Press, Cambridge, MA (1982)

    Google Scholar 

  17. Robu, V., La Poutre., J.: Learning the structure of utility graphs used in negotiation through collaborative filtering. In: Eighth Pacific Rim Workshop on Multi-Agent Systems (PRIMA’05). (2005)

    Google Scholar 

  18. Robu, V., Somefun, D., Poutré, J.A.L.: Modeling complex multi-issue negotiations using utility graphs. In: Fourth International Conference on Autonomous Agents and Multi Agent Systems (AAMAS) (to appear as full paper). (2005)

    Google Scholar 

  19. Sarwar, B., Karypis, G., Konstan, J., Riedl, J.: Item-based collaborative filtering recommendation algorithms. In: Tenth International WWW Conference (WWW10). (2001)

    Google Scholar 

  20. Somefun, D., Klos, T., Poutré, J.L.: Online learning of aggregate knowledge about nonlinear preferences applied to negotiating prices and bundles. In: Proceedings of the Sixth International Conference on E-Commerce. (2004) 361–370

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Robu, V., La Poutré, H. (2008). Constructing the Structure of Utility Graphs Used in Multi-Item Negotiation Through Collaborative Filtering of Aggregate Buyer Preferences. In: Ito, T., Hattori, H., Zhang, M., Matsuo, T. (eds) Rational, Robust, and Secure Negotiations in Multi-Agent Systems. Studies in Computational Intelligence, vol 89. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76282-9_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-76282-9_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-76281-2

  • Online ISBN: 978-3-540-76282-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics