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Collective Voice of Experts in Multilateral Negotiation

Part of the Lecture Notes in Computer Science book series (LNAI,volume 10621)

Abstract

Inspired from the ideas such as “algorithm portfolio”, “mixture of experts”, and “genetic algorithm”, this paper presents two novel negotiation strategies, which combine multiple negotiation experts to decide what to bid and what to accept during the negotiation. In the first approach namely incremental portfolio, a bid is constructed by asking each negotiation agent’s opinion in the portfolio and picking one of the suggestions stochastically considering the expertise levels of the agents. In the second approach namely crossover strategy, each expert agent makes a bid suggestion and a majority voting is used on each issue value to decide the bid content. The proposed approaches have been evaluated empirically and our experimental results showed that the crossover strategy outperformed the top five finalists of the ANAC 2016 Negotiation Competition in terms of the obtained average individual utility.

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Notes

  1. 1.

    http://web.tuat.ac.jp/%7Ekatfuji/ANAC2016/.

  2. 2.

    http://ii.tudelft.nl/genius/.

  3. 3.

    http://web.tuat.ac.jp/~katfuji/ANAC2016/.

References

  1. Alpaydin, E.: Techniques for combining multiple learners. In: Proceedings of Engineering of Intelligent Systems, pp. 6–12 (1998)

    Google Scholar 

  2. Aydoğan, R., Festen, D., Hindriks, K.V., Jonker, C.M.: Alternating offers protocols for multilateral negotiation. In: Fujita, K., Bai, Q., Ito, T., Zhang, M., Ren, F., Aydoğan, R., Hadfi, R. (eds.) Modern Approaches to Agent-based Complex Automated Negotiation. SCI, vol. 674, pp. 153–167. Springer, Cham (2017). doi:10.1007/978-3-319-51563-2_10

    Chapter  Google Scholar 

  3. Aydogan, R., Marsa-Maestre, I., Klein, M., Jonker, C.M.: A machine learning approach for mechanism selection in complex negotiations. In: Proceedings of The 8th International Workshop on Agent-based Complex Automated Negotiations (2015)

    Google Scholar 

  4. Aydoğan, R., Yolum, P.: Effective negotiation with partial preference information. In: Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), Toronto, Canada, May 10–14, 2010, vol. 1–3. pp. 1605–1606 (2010)

    Google Scholar 

  5. Baarslag, T., Gerding, E.H., Aydoğan, R., Schraefel, M.: Optimal negotiation decision functions in time-sensitive domains. In: 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), vol. 2, pp. 190–197. IEEE (2015)

    Google Scholar 

  6. Baarslag, T., Hindriks, K., Jonker, C., 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 (2012). doi:10.1007/978-3-642-24696-8_7

    Chapter  Google Scholar 

  7. Beam, C., Segev, A.: Automated negotiations: a survey of the state of the art. Wirtschaftsinformatik 39(3), 263–268 (1997)

    Google Scholar 

  8. Fatima, S., Kraus, S., Wooldridge, M.: Principles of Automated Negotiation. Cambridge University Press, Cambridge (2014)

    Book  Google Scholar 

  9. Fujita, K., Aydoğan, R., Baarslag, T., Hindriks, K., Ito, T., Jonker, C.: The sixth automated negotiating agents competition (ANAC 2015). In: Fujita, K., Bai, Q., Ito, T., Zhang, M., Ren, F., Aydoğan, R., Hadfi, R. (eds.) Modern Approaches to Agent-based Complex Automated Negotiation. SCI, vol. 674, pp. 139–151. Springer, Cham (2017). doi:10.1007/978-3-319-51563-2_9

    Chapter  Google Scholar 

  10. Fujita, K., et al.: The second automated negotiating agents competition (ANAC2011). In: Ito, T., Zhang, M., Robu, V., Matsuo, T. (eds.) Complex Automated Negotiations: Theories, Models, and Software Competitions. SCI, vol. 435, pp. 183–197. Springer, Heidelberg (2013). doi:10.1007/978-3-642-30737-9_11

    Chapter  Google Scholar 

  11. Ilany, L., Gal, Y.: Algorithm selection in bilateral negotiation. Auton. Agent. Multi-Agent Syst. 30(4), 697–723 (2016)

    Article  Google Scholar 

  12. Jennings, N., Faratin, P., Lomuscio, A., Parsons, S., Wooldridge, M., Sierra, C.: Automated negotiation: prospects, methods and challenges. Group Decis. Negot. 10(2), 199–215 (2001)

    Article  Google Scholar 

  13. Jonker, C.M., Aydoğan, R., Baarslag, T., Fujita, K., Ito, T., Hindriks, K.: Automated negotiating agents competition. In: Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), pp. 5070–5072. AAAI Press (2017)

    Google Scholar 

  14. Lazzaro, J., Ryckebusch, S., Mahowald, M.A., Mead, C.A.: Winner-take-all networks of O (n) complexity. In: Advances in neural information processing systems, pp. 703–711 (1989)

    Google Scholar 

  15. Leyton-Brown, K., Nudelman, E., Andrew, G., McFadden, J., Shoham, Y.: A portfolio approach to algorithm selection. In: IJCAI, pp. 1542–1543 (2003)

    Google Scholar 

  16. Lin, R., Kraus, S., Baarslag, T., Tykhonov, D., Hindriks, K., Jonker, C.M.: Genius: an integrated environment for supporting the design of generic automated negotiators. Comput. Intell. 30(1), 48–70 (2014)

    Article  MathSciNet  Google Scholar 

  17. Marsa-Maestre, I., Klein, M., Jonker, C.M., Aydoğan, R.: From problems to protocols: towards a negotiation handbook. Decis. Support Syst. 60, 39–54 (2014)

    Article  Google Scholar 

  18. Melanie, M.: An Introduction to Genetic Algorithms, vol. 5, pp. 62–75. MIT Press, Cambridge, London (1999)

    Google Scholar 

  19. Rice, J.R.: The algorithm selection problem. Adv. Comput. 15, 65–118 (1976). Elsevier

    Article  Google Scholar 

  20. Sanchez-Anguix, V., Aydogan, R., Julian, V., Jonker, C.: Unanimously acceptable agreements for negotiation teams in unpredictable domains. Electron. Commer. Res. Appl. 13(4), 243–265 (2014)

    Article  Google Scholar 

  21. Sierra, C., Faratin, P., Jennings, N.R.: A service-oriented negotiation model between autonomous agents. In: Padget, J.A. (ed.) Collaboration between Human and Artificial Societies 1997. LNCS, vol. 1624, pp. 201–219. Springer, Heidelberg (1999). doi:10.1007/10703260_12

    Chapter  Google Scholar 

  22. Williams, C.R., Robu, V., Gerding, E.H., Jennings, N.R.: An overview of the results and insights from the third automated negotiating agents competition (ANAC2012). In: Marsa-Maestre, I., Lopez-Carmona, M.A., Ito, T., Zhang, M., Bai, Q., Fujita, K. (eds.) Novel Insights in Agent-based Complex Automated Negotiation. SCI, vol. 535, pp. 151–162. Springer, Tokyo (2014). doi:10.1007/978-4-431-54758-7_9

    Chapter  Google Scholar 

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Acknowledgments

We thank Burak Atalay and Bahadır Kırdan for their help in implementation of the initial agent. This work was supported by the ITEA M2MGrids Project, grant number ITEA141011.

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Correspondence to Taha D. Güneş .

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Güneş, T.D., Arditi, E., Aydoğan, R. (2017). Collective Voice of Experts in Multilateral Negotiation. In: An, B., Bazzan, A., Leite, J., Villata, S., van der Torre, L. (eds) PRIMA 2017: Principles and Practice of Multi-Agent Systems. PRIMA 2017. Lecture Notes in Computer Science(), vol 10621. Springer, Cham. https://doi.org/10.1007/978-3-319-69131-2_27

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  • DOI: https://doi.org/10.1007/978-3-319-69131-2_27

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