Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content
Springer Nature Link
Log in

Using GDL to Represent Domain Knowledge for Automated Negotiations

  • Conference paper
  • First Online:
Autonomous Agents and Multiagent Systems (AAMAS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10003))

Included in the following conference series:

  • 581 Accesses

Abstract

Current negotiation algorithms often assume that utility has an explicit representation as a function over the set of possible deals and that for any deal its utility value can be calculated easily. We argue however, that a more realistic model of negotiations would be one in which the negotiator has certain knowledge about the domain and must reason with this knowledge in order to determine the value of a deal, which is time-consuming. We propose to use Game Description Language to model such negotiation scenarios, because this may enable us to apply existing techniques from General Game Playing to implement domain-independent, reasoning, negotiation algorithms.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Similar content being viewed by others

Notes

  1. 1.

    http://sanchoggp.blogspot.co.uk/2014/05/what-is-sancho.html.

  2. 2.

    https://bitbucket.org/rxe/galvanise_v2.

  3. 3.

    We could generalize this and allow protocols in which more than one deal can be made. However, we will not do so here for simplicity.

  4. 4.

    We should stress here that we have assumed agreements are binding. Without this assumption this statement would not be true.

  5. 5.

    GDL defines more relations, but these are not relevant for this paper.

References

  1. Baarslag, T., Hindriks, K., Jonker, C.M., Kraus, S., Lin, R.: The first automated negotiating agents competition (ANAC 2010). In: Ito, T., Zhang, M., Robu, V., Fatima, S., Matsuo, T. (eds.) New Trends in Agent-based Complex Automated Negotiations. SCI, vol. 383, pp. 113–135. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  2. Ceri, S., Gottlob, G., Tanca, L.: What you always wanted to know about datalog (and never dared to ask). IEEE Trans. Knowl. Data Eng. 1(1), 146–166 (1989)

    Article  Google Scholar 

  3. Fabregues, A.: Facing the challenge of automated negotiations with humans. Ph.D. thesis, Universitat Autònoma de Barcelona (2012)

    Google Scholar 

  4. Fabregues, A., Sierra, C.: DipGame: a challenging negotiation testbed. Eng. Appl. Artif. Intell. 24, 1137–1146 (2011)

    Article  Google Scholar 

  5. Faratin, P., Sierra, C., Jennings, N.R.: Using similarity criteria to make negotiation trade-offs. In: International Conference on Multi-Agent Systems, ICMAS 2000, pp. 119–126 (2000)

    Google Scholar 

  6. Faratin, P., Sierra, C., Jennings, N.R.: Negotiation decision functions for autonomous agents. Robot. Auton. Syst. 24(3–4), 159–182 (1998). Multi-AgentRationality. http://www.sciencedirect.com/science/article/pii/S0921889098000293

    Article  Google Scholar 

  7. Fatima, S., Wooldridge, M., Jennings, N.R.: An analysis of feasible solutions for multi-issue negotiation involving nonlinear utility functions. In: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2009, vol. 2. pp. 1041–1048. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2009). http://dl.acm.org/citation.cfm?id=1558109.1558158

  8. Ferreira, A., Lopes Cardoso, H., Paulo Reis, L.: DipBlue: a diplomacy agent with strategic and trust reasoning. In: 7th International Conference on Agents and Artificial Intelligence (ICAART 2015), pp. 398–405 (2015)

    Google Scholar 

  9. Finnsson, H.: Simulation-based general game playing. Ph.D. thesis, School of Computer Science, Reykjavik University (2012)

    Google Scholar 

  10. Genesereth, M., Love, N., Pell, B.: General game playing: overview of the AAAI competition. AI Mag. 26(2), 62–72 (2005)

    Google Scholar 

  11. Genesereth, M.R., Thielscher, M.: General Game Playing. Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool Publishers, San Rafael (2014)

    MATH  Google Scholar 

  12. Ito, T., Klein, M., Hattori, H.: A multi-issue negotiation protocol among agents with nonlinear utility functions. Multiagent Grid Syst. 4, 67–83 (2008). http://dl.acm.org/citation.cfm?id=1378675.1378678

    Article  MATH  Google Scholar 

  13. de Jonge, D.: Negotiations over large agreement spaces. Ph.D. thesis, Universitat Autònoma de Barcelona (2015)

    Google Scholar 

  14. de Jonge, D., Sierra, C.: NB3: a multilateral negotiation algorithm for large, non-linear agreement spaces with limited time. Auton. Agents Multi-Agent Syst. 29(5), 896–942 (2015). http://www.iiia.csic.es/files/pdfs/jaamas%20NB3.pdf

  15. Knuth, D.E., Moore, R.W.: An analysis of alpha-beta pruning. Artif. Intell. 6(4), 293–326 (1975). http://www.sciencedirect.com/science/article/pii/0004370275900193

    Google Scholar 

  16. Kocsis, L., Szepesvári, C.: Bandit based Monte-Carlo planning. In: Fürnkranz, J., Scheffer, T., Spiliopoulou, M. (eds.) ECML 2006. LNCS (LNAI), vol. 4212, pp. 282–293. Springer, Heidelberg (2006). doi:10.1007/11871842_29

    Chapter  Google Scholar 

  17. Kraus, S.: Designing and building a negotiating automated agent. Comput. Intell. 11, 132–171 (1995)

    Article  Google Scholar 

  18. Love, N., Genesereth, M., Hinrichs, T.: General game playing: game description language specification. Technical report LG-2006-01, Stanford University, Stanford, CA (2006). http://logic.stanford.edu/reports/LG-2006-01.pdf

  19. Marsa-Maestre, I., Lopez-Carmona, M.A., Velasco, J.R., de la Hoz, E.: Effective bidding and deal identification for negotiations in highly nonlinear scenarios. In: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2009, vol. 2, pp. 1057–1064. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2009). http://dl.acm.org/citation.cfm?id=1558109.1558160

  20. Marsa-Maestre, I., Lopez-Carmona, M.A., Velasco, J.R., Ito, T., Klein, M., Fujita, K.: Balancing utility and deal probability for auction-based negotiations in highly nonlinear utility spaces. In: Proceedings of the 21st International Jont Conference on Artifical Intelligence, IJCAI 2009, pp. 214–219. Morgan Kaufmann Publishers Inc., San Francisco (2009). http://dl.acm.org/citation.cfm?id=1661445.1661480

  21. Nash, J.: The bargaining problem. Econometrica 18, 155–162 (1950)

    Article  MathSciNet  MATH  Google Scholar 

  22. von Neumann, J.: On the theory of games of strategy. In: Tucker, A., Luce, R. (eds.) Contributions to the Theory of Games, pp. 13–42. Princeton University Press, Princeton (1959)

    Google Scholar 

  23. Rosenschein, J.S., Zlotkin, G.: Rules of Encounter. The MIT Press, Cambridge (1994)

    MATH  Google Scholar 

  24. Kraus, S., Lehman, D., Ephrati, E.: An automated diplomacy player. In: Levy, D., Beal, D. (eds.) Heuristic Programming in Artificial Intelligence: The 1st Computer Olympia, pp. 134–153. Ellis Horwood Limited, Chichester (1989)

    Google Scholar 

  25. Schiffel, S., Thielscher, M.: M.: Fluxplayer: a successful general game player. In: Proceedings of the AAAI National Conference on Artificial Intelligence, pp. 1191–1196. AAAI Press (2007)

    Google Scholar 

  26. Serrano, R.: Bargaining. In: Durlauf, S.N., Blume, L.E. (eds.) The New Palgrave Dictionary of Economics. Palgrave Macmillan, Basingstoke (2008)

    Google Scholar 

  27. Thielscher, M.: A general game description language for incomplete information games. In: Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2010, 11–15 July 2010, Atlanta, Georgia, USA (2010). http://www.aaai.org/ocs/index.php/AAAI/AAAI10/paper/view/1727

  28. Zhang, D., Thielscher, M.: A logic for reasoning about game strategies. In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI 2015), pp. 1671–1677 (2015)

    Google Scholar 

Download references

Acknowledgments

This work was sponsored by an Endeavour Research Fellowship awarded by the Australian Government, Department of Education.

Author information

Authors and Affiliations

  1. Artificial Intelligence Research Group, Western Sydney University, Penrith, NSW, 2751, Australia

    Dave de Jonge & Dongmo Zhang

Authors
  1. Dave de Jonge
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dongmo Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dave de Jonge .

Editor information

Editors and Affiliations

  1. Campus de la UAB, IIIA-CSIC, Bellaterra, Spain

    Nardine Osman

  2. Campus de la UAB, IIIA-CSIC, Cerdanyola, Spain

    Carles Sierra

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing AG

About this paper

Cite this paper

de Jonge, D., Zhang, D. (2016). Using GDL to Represent Domain Knowledge for Automated Negotiations. In: Osman, N., Sierra, C. (eds) Autonomous Agents and Multiagent Systems. AAMAS 2016. Lecture Notes in Computer Science(), vol 10003. Springer, Cham. https://doi.org/10.1007/978-3-319-46840-2_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-46840-2_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46839-6

  • Online ISBN: 978-3-319-46840-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation