Autonomous Agent that Provides Automated Feedback Improves Negotiation Skills

  • Shannon Monahan
  • Emmanuel Johnson
  • Gale LucasEmail author
  • James Finch
  • Jonathan Gratch
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10948)


Research has found that individuals can improve their negotiation abilities by practicing with virtual agents [1, 2]. For these pedagogical agents to become more “intelligent,” the system should be able to give feedback on negotiation performance [3, 4]. In this study, we examined the impact of providing such individualized feedback. Participants first engaged in a negotiation with a virtual agent. After this negotiation, participants were either given automated individualized feedback or not. Feedback was based on negotiation principles [4], which were quantified using a validated approach [5]. Participants then completed a second, parallel negotiation. Our results show that, compared to the control condition, participants who received such feedback after the first negotiation showed a significantly greater improvement in the strength of their first offer, concession curve, and thus their final outcome in the negotiation.


Negotiation Individualized feedback Automated metrics 



This research was supported by the US Army and the National Science Foundation. The content does not necessarily reflect the position or the policy of any Government, and no official endorsement should be inferred.


  1. 1.
    Gratch, J., DeVault, D., Lucas, G.: The benefits of virtual humans for teaching negotiation. In: Traum, D., Swartout, W., Khooshabeh, P., Kopp, S., Scherer, S., Leuski, A. (eds.) IVA 2016. LNCS (LNAI), vol. 10011, pp. 283–294. Springer, Cham (2016). Scholar
  2. 2.
    Lin, R., Oshrat, Y., Kraus, S.: Investigating the benefits of automated negotiations in enhancing people’s negotiation skills. In: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems-Volume 1, pp. 345–352. International Foundation for Autonomous Agents and Multiagent Systems, May 2009Google Scholar
  3. 3.
    Kolb, A.Y., Kolb, D.A.: Experiential learning theory. In: Encyclopedia of the Sciences of Learning, pp. 1215–1219. Springer USGoogle Scholar
  4. 4.
    Kelley, H.H.: A classroom study of the dilemmas in interpersonal negotiations. Berkeley Institute of International Studies, University of California (1966)Google Scholar
  5. 5.
    Johnson, E., Gratch, J., DeVault, D.: Towards an autonomous agent that provides automated feedback on students’ negotiation skills. In: Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, pp. 410–418. International Foundation for Autonomous Agents and Multiagent Systems, May 2017Google Scholar
  6. 6.
    Rosen, Y.: Assessing students in human-to-agent settings to inform collaborative problem-solving learning. J. Educ. Meas. 54(1), 36–53 (2017)CrossRefGoogle Scholar
  7. 7.
    Graesser, A.C., Cai, Z., Hu, X., Foltz, P.W., Greiff, S., Kuo, B.C., Shaffer, D.W.: Assessment of collaborative problem solving. Des. Recomm. Intell. Tutoring Syst. 275 (2017)Google Scholar
  8. 8.
    O’Neil, H.F., Chuang, S.S., Baker, E.L.: Computer-based feedback for computer-based collaborative problem solving. In: Ifenthaler, D., Pirnay-Dummer, P., Seel, N. (eds.) Computer-Based Diagnostics and Systematic Analysis of Knowledge, pp. 261–279. Springer, Boston (2010). Scholar
  9. 9.
    Hall, R.L.: Measuring legislative influence. Legis. Stud. Q. 17(2), 205–231 (1992)CrossRefGoogle Scholar
  10. 10.
    Wunderle, W.: How to negotiate in the middle east. Mil. Rev. 87(2), 33 (2007)Google Scholar
  11. 11.
    Eisenberg, T., Lanvers, C.: What is the settlement rate and why should we care? J. Empir. Leg. Stud. 6(1), 111–146 (2009)CrossRefGoogle Scholar
  12. 12.
    Samborn, H.V.: Vanishing trial, the. ABAJ 88, 24 (2002)Google Scholar
  13. 13.
    Movius, H.: The effectiveness of negotiation training. Negotaiation J. 24(4), 509–531 (2008)CrossRefGoogle Scholar
  14. 14.
    Hattie, J., Timperley, H.: The power of feedback. Review of educational research 77(1), 81–112 (2007)CrossRefGoogle Scholar
  15. 15.
    DeVault, D., Mell, J., Gratch, J.: Toward natural turn-taking in a virtual human negotiation agent. In: AAAI Spring Symposium on Turn-taking and Coordination in Human-Machine Interaction. AAAI Press, Stanford, March 2015Google Scholar
  16. 16.
    Hartholt, A., Traum, D., Marsella, Stacy C., Shapiro, A., Stratou, G., Leuski, A., Morency, L.-P., Gratch, J.: All together now. In: Aylett, R., Krenn, B., Pelachaud, C., Shimodaira, H. (eds.) IVA 2013. LNCS (LNAI), vol. 8108, pp. 368–381. Springer, Heidelberg (2013). Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Shannon Monahan
    • 1
  • Emmanuel Johnson
    • 2
  • Gale Lucas
    • 2
    Email author
  • James Finch
    • 3
  • Jonathan Gratch
    • 2
  1. 1.The American University of ParisParisFrance
  2. 2.University of Southern CaliforniaLos AngelesUSA
  3. 3.Michigan State UniversityEast LansingUSA

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