Skip to main content

Using and Evaluating Adaptive Agents for Electronic Commerce Negotiation

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNAI,volume 1952)

Abstract

Agent technology has been applied to the Electronic Commerce domain, giving birth to what is known as agent-mediated Electronic Commerce. Current real-world applications refer only to the delegation of product or merchant brokering tasks to software agents. Automated negotiation is a less explored stage in this field, since it implies the trust of bargaining power to software agents. We here present SMACE, a layered platform for agent- mediated Electronic Commerce, supporting multilateral and multi-issue automated negotiations. In this system, the negotiation infrastructure through which the software agents interact is independent from their negotiation strategies. SMACE has been used to test several negotiation strategies. The system includes agents that are capable of increasing their performance with their own experience, by adapting to the market conditions. This adaptation is reached through the use of Reinforcement Learning techniques. In order to test the agents’ adaptation process, several different experiments have been tried out, and the respective results are here reported. These results allow us to conclude that it is possible to build negotiation strategies that can outperform others in some environments. In fact, knowledge gathered about past negotiations can be a strategic advantage in some scenarios.

Keywords

  • multi-agent systems
  • electronic commerce
  • automated negotiation
  • automated learning

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/3-540-44399-1_11
  • Chapter length: 10 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   109.00
Price excludes VAT (USA)
  • ISBN: 978-3-540-44399-5
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   139.00
Price excludes VAT (USA)

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bosak, J. (1997), „XML, Java, and the future of the Web”, Sun Microsystems.

    Google Scholar 

  2. Chavez, A., D. Dreilinger, R. Guttman and P. Maes (1997), „A Real-Life Experiment in Creating an Agent Marketplace”, in Proceedings of the Second International Conference on the Practical Application of Intelligent Agents and Multi-Agent Technology (PAAM’97).

    Google Scholar 

  3. Chavez, A, and P. Maes (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 (PAAM’96), pp. 75–90.

    Google Scholar 

  4. Faratin, P., C. Sierra and N.R. Jennings (1998), „Negotiation Decision Functions for Autonomous Agents”, International Journal of Robotics and Autonomous Systems, 24 (3–4), pp. 159–182.

    CrossRef  Google Scholar 

  5. Finin, T., Y. Labrou and J. Mayfield (1997), „KQML as an agent communication language”, in Software Agents, J. M. Bradshaw (editor), MIT Press.

    Google Scholar 

  6. Guttman, R.H., A.G. Moukas and P. Maes (1998), „Agent-mediated Electronic Commerce: A Survey”, Knowledge Engineering Review.

    Google Scholar 

  7. Matos, N., C. Sierra and N.R. Jennings (1998), „Determining Successful Negotiation Strategies: An Evolutionary Approach”, in Proceedings, Third International Conference on Multi-Agent Systems (ICMAS-98), pp. 182–189, IEEE Computer Society.

    Google Scholar 

  8. Parsons S., C. Sierra and N.R. Jennings (1998), „Agents that reason and negotiate by arguing”, in Journal of Logic and Computation, 8 (3), pp. 261–292.

    MATH  CrossRef  MathSciNet  Google Scholar 

  9. Romm, C.T. and F. Sudweeks (1998), Doing Business Electronically, London: Springer-Verlag.

    Google Scholar 

  10. Sutton, R.S. and A.G. Barto (1998), Reinforcement Learning: An Introduction, Cambridge: MIT Press.

    Google Scholar 

  11. Wurman, P.R., M.P. Wellman and W.E. Walsh (1998), „The Michigan Internet AuctionBot: A Configurable Auction Server for Human and Software Agents”, in Proceedings of the Second International Conference on Autonomous Agents (Agents’98), K.P. Sycara and M. Wooldridge (editors), pp. 301–308, ACM Press.

    Google Scholar 

  12. Zeng, D. and K. Sycara (1996), „How Can an Agent Learn to Negotiate?”, in Intelligent Agents III, J. P. Muller et al. (editors), pp. 233–244, Springer-Verlag.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2000 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Lopes Cardoso, H., Oliveira, E. (2000). Using and Evaluating Adaptive Agents for Electronic Commerce Negotiation. In: Monard, M.C., Sichman, J.S. (eds) Advances in Artificial Intelligence. IBERAMIA SBIA 2000 2000. Lecture Notes in Computer Science(), vol 1952. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44399-1_11

Download citation

  • DOI: https://doi.org/10.1007/3-540-44399-1_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41276-2

  • Online ISBN: 978-3-540-44399-5

  • eBook Packages: Springer Book Archive