Skip to main content

Fixed-pie Lie in Action

  • Conference paper
  • First Online:
Intelligent Virtual Agents (IVA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10498))

Included in the following conference series:

Abstract

Negotiation is a crucial skill for socially intelligent agents. Sometimes negotiators lie to gain advantage. In particular, they can claim that they want the same thing as their opponents (i.e., use a “fixed-pie lie”) to gain an advantage while appearing fair. The current work is the first attempt to examine effectiveness of this strategy when used by agents against humans in realistic negotiation settings. Using the IAGO platform, we show that the exploitative agent indeed wins more points while appearing fair and honest to its opponent. In a second study, we investigated how far the exploitative agents could push for more gain and examined their effect on people’s behavior. This study shows that even though exploitative agents gained high value in short-term, their long-term success remains questioned as they left their opponents unhappy and unsatisfied.

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

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Baarslag, T., Kaisers, M., Gerding, E.H., Jonker, C.M., Gratch, J.: When will negotiation agents be able to represent us the challenges and opportunities for autonomous negotiators. In: Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (2017)

    Google Scholar 

  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, vol. 1, pp. 345–352 (2009)

    Google Scholar 

  3. Core, M., Traum, D., Lane, H.C., Swartout, W., Gratch, J., van Lent, M., Marsella, S.: Teaching negotiation skills through practice and reflection with virtual humans. Simulation 82(11), 685–701 (2006)

    Article  Google Scholar 

  4. Broekens, J., Harbers, M., Brinkman, W.-P., Jonker, C.M., Van den Bosch, K., Meyer, J.-J.: Virtual reality negotiation training increases negotiation knowledge and skill. In: Nakano, Y., Neff, M., Paiva, A., Walker, M. (eds.) IVA 2012. LNCS, vol. 7502, pp. 218–230. Springer, Heidelberg (2012). doi:10.1007/978-3-642-33197-8_23

    Chapter  Google Scholar 

  5. Gratch, J., DeVault, D., Lucas, G.M., Marsella, S.: Negotiation as a challenge problem for virtual humans. In: Brinkman, W.-P., Broekens, J., Heylen, D. (eds.) IVA 2015. LNCS, vol. 9238, pp. 201–215. Springer, Cham (2015). doi:10.1007/978-3-319-21996-7_21

    Chapter  Google Scholar 

  6. Osborne, M.J., Rubinstein, A.: A course in game theory. MIT Press (1994)

    Google Scholar 

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

    Article  Google Scholar 

  8. Thompson, L.L.: Information exchange in negotiation. J. Exp. Soc. Psychol. 27(2), 161–179 (1991)

    Article  Google Scholar 

  9. Gratch, J., Nazari, Z., Johnson, E.: The misrepresentation game: how to win at negotiation while seeming like a nice guy. In: Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, pp. 728–737 (2016)

    Google Scholar 

  10. Mell, J., Gratch, J.: IAGO: interactive arbitration guide online. In: Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, pp. 1510–1512 (2016)

    Google Scholar 

  11. Nazari, Z., Lucas, G.M., Gratch, J.: Opponent modeling for virtual human negotiators. In: Brinkman, W.-P., Broekens, J., Heylen, D. (eds.) IVA 2015. LNCS, vol. 9238, pp. 39–49. Springer, Cham (2015). doi:10.1007/978-3-319-21996-7_4

    Chapter  Google Scholar 

  12. Baarslag, T., Hendrikx, M., Hindriks, K., Jonker, C.: Predicting the performance of opponent models in automated negotiation. In: Proc. - 2013 IEEE/WIC/ACM Int. Conf. Intell. Agent Technol. IAT 2013, vol. 2, pp. 59–66 (2013)

    Google Scholar 

  13. Gratch, J., Nguyen, T.: Misrepresentation Negotiation Games. Univ. South. Calif. Inst. Creat. Technol. Play, Vista (2016)

    Google Scholar 

  14. Reilly, P.R.: Was Machiavelli right? Lying in negotiation and the art of defensive self-help (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zahra Nazari .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Nazari, Z., Lucas, G., Gratch, J. (2017). Fixed-pie Lie in Action. In: Beskow, J., Peters, C., Castellano, G., O'Sullivan, C., Leite, I., Kopp, S. (eds) Intelligent Virtual Agents. IVA 2017. Lecture Notes in Computer Science(), vol 10498. Springer, Cham. https://doi.org/10.1007/978-3-319-67401-8_38

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-67401-8_38

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67400-1

  • Online ISBN: 978-3-319-67401-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics