Bilateral Negotiation of a Meeting Point in a Maze: Demonstration

  • Fabien Delecroix
  • Maxime Morge
  • Jean-Christophe Routier
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8473)


Negotiation between agents aims at reaching an agreement in which the conflicting interests of agents are accommodated. In this demonstration, we present a concrete negotiation scenario where two agents are situated in a maze and the negotiation outcome is a cell where they will meet. Their individual preferences match with a minimal distance computed from their partial knowledge of the environment. We illustrate a bargaining protocol which allows agents to submit several proposals at the same round and a negotiation strategy which consists in starting from the best deal for the agent and then concedes. The path between the agents emerges from the repeated negotiations.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Rosenschein, J., Zlotkin, G.: Rules of Encounter - Designing Conventions for Automated Negotiation among Computers. MIT Press (1994)Google Scholar
  2. 2.
    Rubinstein, A.: Perfect equilibrium in a bargaining model. Econometrica 50(1), 97–102 (1982)CrossRefzbMATHMathSciNetGoogle Scholar
  3. 3.
    Fatima, S.S., Wooldridge, M., Jennings, N.R.: Multi-issue negotiation with deadlines. Journal of Artificial Intelligence Research 27, 381–417 (2006)zbMATHMathSciNetGoogle Scholar
  4. 4.
    Gatti, N., Giunta, F.D., Marino, S.: Alternating-offers bargaining with one-sided uncertain deadlines: an efficient algorithm. Artificial Intelligence 172(8-9), 1119–1157 (2008)CrossRefzbMATHMathSciNetGoogle Scholar
  5. 5.
    Sandholm, T., Vulkan, N.: Bargaining with deadlines. In: Proc. of AAAI, pp. 44–51 (1999)Google Scholar
  6. 6.
    Faratin, P., Sierra, C., Jennings, N.R.: Negotiation decision functions for autonomous agents. Robotics and Autonomous Systems 24(3-4), 159–182 (1998)CrossRefGoogle Scholar
  7. 7.
    Morge, M., Picard, G.: Privacy-preserving strategy for negotiating stable, equitable and optimal matchings. In: Demazeau, Y., Pěchoucěk, M., Corchado, J.M., Pérez, J.B. (eds.) Adv. on Prac. Appl. of Agents and Multi. Sys. AISC, pp. 97–102. Springer, Heidelberg (2011)Google Scholar
  8. 8.
    Aydoğan, R., Baarslag, T., Hindriks, K.V., Jonker, C.M., Yolum, P.: Heuristic-based approaches for CP-nets in negotiation. In: Ito, T., Zhang, M., Robu, V., Matsuo, T. (eds.) Complex Automated Negotiations. SCI, vol. 435, pp. 115–126. Springer, Heidelberg (2012)Google Scholar
  9. 9.
    Jennings, N., Faratin, P., Lomuscio, A., Parsons, S., Wooldridge, M., Sierra, C.: Automated negotiation: Prospects methods and challenges. Group Decision and Negotiation 10(2), 199–215 (2001)CrossRefGoogle Scholar
  10. 10.
    Delecroix, F., Morge, M., Routier, J.C.: Bilateral negotiation of a meeting point in a maze. In: Demazeau, Y., Corchado, J.M., Zambonelli, F., Bajo, J. (eds.) PAAMS 2014. LNCS (LNAI), vol. 8473, pp. 86–97. Springer, Heidelberg (2014)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Fabien Delecroix
    • 1
  • Maxime Morge
    • 1
  • Jean-Christophe Routier
    • 1
  1. 1.Laboratoire d’Informatique Fondamentale de LilleUniversité Lille 1, Cité ScientifiqueVilleneuve d’AscqFrance

Personalised recommendations