Abstract
Most real-world negotiation involves multiple interdependent issues, which create agent utility functions that are nonlinear. In this paper, we employ utility functions based on “cone-constraints,” which is more realistic than previous formulations. Cone-constraints capture the intuition that agents’ utilities for a contract usually decline gradually, rather than step-wise, with distance from their ideal contract. In addition, one of the main challenges in developing effective nonlinear negotiation protocols is scalability; they can produce excessively high failure rates, when there are many issues, due to computational intractability. In this paper, we propose the scalable and efficient protocols by grouping Issues. Our protocols can reduce computational cost, while maintaining good quality outcomes, with decomposing the utility space into several largely independent sub-spaces. We also demonstrate that our proposed protocol is highly scalable when compared to previous efforts in a realistic experimental setting.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Fatima, S.S., Wooldridge, M., Jennings, N. R.: An analysis of feasible solutions for multi-issue negotiation involving nonlinear utility functions. In: Proc. of the Eighth International Joint Conference on Autonomous Agents and Multi-agent Systems (AAMAS 2009), pp. 1041–1048 (2009)
Fujita, K., Ito, T., Klein, M.: A representative-based multi-round protocol for multi-issue negotiations. In: Proc. of the Seventh International Joint Conference on Autonomous Agents and Multi-agent Systems (AAMAS 2008), pp. 1573–1576 (2008)
Fujita, K., Ito, T., Klein, M.: A secure and fair negotiation protocol in highly complex utilityspace based on cone-constraints. In: Proc. of the 2009 International Joint Conference on Intelligent Agent Technology, IAT 2009 (2009); (short Paper)
Gerding, E., Somefun, D., Poutre, H.L.: Efficient methods for automated multi-issue negotiation: Negotiating over a two-part tariff. International Journal of Intelligent Systems 21, 99–119 (2006)
Greenstadt, R., Pearce, J., Tambe, M.: Analysis of privacy loss in distributed constraint optimization. In: Proc. of the 21th Association for the Advancement of Artificial Intelligence (AAAI 2006), pp. 647–653 (2006)
Hindriks, K.V., Jonker, C.M., Tykhonov, D.: Eliminating Interdependencies Between Issues for Multi-issue Negotiation. In: Klusch, M., Rovatsos, M., Payne, T.R. (eds.) CIA 2006. LNCS (LNAI), vol. 4149, pp. 301–316. Springer, Heidelberg (2006)
Ito, T., Hattori, H., Klein, M.: Multi-issue negotiation protocol for agents: Exploring nonlinear utility spaces. In: Proc. of the 20th International Joint Conference on Artificial Intelligence (IJCAI 2007), pp. 1347–1352 (2007)
Klein, M., Faratin, P., Sayama, H., Bar-Yam, Y.: Negotiating complex contracts. Group Decision and Negotiation 12(2), 58–73 (2003)
Kraus, S.: Strategic Negotiation in Multiagent Environments. Cambridge University Press (2001)
Lai, G., Li, C., Sycara, K.: A pareto optimal model for automated multi-attribute negotiations. In: Proc. of the Sixth International Joint Conference on Autonomous Agents and Multi-agent Systems (AAMAS 2007), pp. 1040–1042 (2007)
Li, M., Vo, Q.B., Kowalczyk, R.: Searching for fair joint gains in agent-based negotiation. In: Proc. of the Eighth International Joint Conference on Autonomous Agents and Multi-agent Systems (AAMAS 2009), pp. 1049–1056 (2009)
Lin R.J., Chou S.T.: Bilateral multi-issue negotiations in a dynamic environment. In: Proc. of the AAMAS Workshop on Agent Mediated Electronic Commerce (AMEC 2003) (2003)
Maheswaran, R.T., Pearce, J.P., Varakantham, P., Bowring, E.: Valuations of possible states (vps):a quantitative framework for analysis of privacy loss among collaborative personal assistant agents. In: Proc. of the Forth Inernational Joint Conference on Autonomous Agents and Multi-agent Systems (AAMAS 2005), pp. 1030–1037 (2005)
Malone, T.W., Klein, M.: Harnessing collective intelligence to address global climate change. Innovations Journal 2(3), 15–26 (2007)
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: Proc. of the Eighth International Joint Conference on Autonomous Agents and Multi-agent Systems (AAMAS 2009), pp. 1057–1064 (2009)
Marsa-Maestre, I., Lopez-Carmona, M.A., Velasco, J.R., Ito, T., Fujita, K., Klein, M.: Balancing utility and deal probability for negotiations in highly nonlinear utility spaces. In: Proc. of the Twenty-first International Joint Conference on Artificial Intelligence (IJCAI 2009), pp. 214–219 (2009)
Robu, V., Poutre, H.L.: Retrieving the structure of utility graphs used in multi-item negotiation through collaborative filtering of aggregate buyer preferences. In: Proc. of the 2nd International Workshop on Rational, Robust, and Secure Negotiations in Multi-Agent Systems, RRS 2006 (2006)
Robu, V., Somefun, D.J.A., Poutre, J.L.: Modeling complex multi-issue negotiations using utility graphs. In: Proc. of the 4th International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2005), pp. 280–287 (2005)
Russell, S.J., Norvig, P.: Artificial Intelligence: A Modern Approach. Prentice-Hall (2002)
Zhang, D.: Axiomatic characterization of task oriented negotiation. In: Proc. of the Twenty-first International Joint Conference on Artificial Intelligence (IJCAI 2009), pp. 367–372 (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Fujita, K., Ito, T., Klein, M. (2012). The Effect of Grouping Issues in Multiple Interdependent Issues Negotiation based on Cone-Constraints. In: Ito, T., Zhang, M., Robu, V., Fatima, S., Matsuo, T. (eds) New Trends in Agent-Based Complex Automated Negotiations. Studies in Computational Intelligence, vol 383. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24696-8_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-24696-8_3
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24695-1
Online ISBN: 978-3-642-24696-8
eBook Packages: EngineeringEngineering (R0)