Skip to main content

Individual Rationality and Real-World Strategic Interactions: Understanding the Competitive-Cooperative Spectrum

  • Conference paper
  • First Online:
  • 1265 Accesses

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 858))

Abstract

We are interested in game-theoretic models of (bounded) rationality, and specifically in investigating (in)adequacy of the traditional models of rational behavior in strategic encounters – models such as Nash Equilibria and other “solution concepts” from the classical game theory. We argue that classical game theory arose in the historical and social context dominated by the Cold War and interest in zero-sum games, leading to solution concepts appropriate for the competitive games (either strictly competitive or at least, “close to being zero-sum”), but that have been found to be woefully inadequate when applied to certain 2-player games that are “far away” from being zero-sum, that is, farther along the spectrum ranging from strict competition to complete cooperation. We share some insights and our (perhaps in some cases provocative!) thoughts inspired by both prior research on an interesting 2-player game, Iterated Traveler’s Dilemma, and recent political developments in the United States of America and around the globe, arguing that, for strategic encounters that inherently value cooperative behavior, most existing solution concepts appear grossly inadequate as satisfactory models of individual rationality – and that new concepts of “solutions”, that is, of what it means to act rationally, are direly needed for such strategic interactions.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Basu, K.: The Traveler’s Dilemma: paradoxes of rationality in game theory. Amer. Econ. Rev. 84(2), 391–395 (1994)

    Google Scholar 

  2. Axelrod, R.: Effective choice in the prisoner’s Dilemma. J. Confl. Resolut. 24(1), 3–25 (1980)

    Article  Google Scholar 

  3. Capra, C.M., Goeree, J.K., Gomez, R., Holt, C.A.: Anomalous behavior in a Traveler’s Dilemma? Am. Econ. Rev. 89(3), 678–690 (1999)

    Article  Google Scholar 

  4. Osborne, M.: An Introduction to Game Theory. Oxford University Press, New York (2004)

    Google Scholar 

  5. Tosic, P., Dasler, P.: Strategies for challenging two-player games: some lessons from iterated traveler’s Dilemma. In: Proceedings 4th International Conference on Agents & Artificial Intelligence (ICAART-12), Algarve, Portugal (2012)

    Google Scholar 

  6. Tosic, P., Dasler, P., Ordonez, C.: On finding and learning effective strategies for complex non-zero-sum repeated games. In: Proceedings IEEE / WIC / ACM International Conference Web Intelligence & Intelligent Agent Technology (WI-IAT 2012). IEEE Computer Society, Macau (2012)

    Google Scholar 

  7. Tosic, P., Dasler, P.: How to play well in non-zero sum games: some lessons from generalized traveler’s Dilemma. In: Zhong, N., Callaghan, V., Ghorbani, A., Hu, B. (eds.) Active Media Technology (AMT-2011), LNCS, vol. 6890, pp 300–311. Springer (2011)

    Google Scholar 

  8. Halpern, J., Pass, R.: Iterated regret minimization: a new solution concept. In: Proceedings 21st International Joint Conference Artificial Intelligence, (IJCAI 2009), San Francisco, California, USA, pp. 153–158 (2009)

    Google Scholar 

  9. Halpern, J., Pass, R.: Iterated regret minimization: a new solution concept. Games Econ. Behav. 74, 184–207 (2012)

    Article  MathSciNet  Google Scholar 

  10. Pace, M.: How a genetic algorithm learns to play Traveler’s Dilemma by choosing dominated strategies to achieve greater payoffs. In: Proceedings Symposium Computational Intelligence & Games (CIG 2009), pp. 194–200. IEEE (2009)

    Google Scholar 

  11. Tosic, P.: Reputation-based distributed coordination for heterogeneous autonomous agents. In: Proceedings Internet of Agents (IoA-2016) Workshop, within Web Intelligence Workshops (WIW-2016), Omaha, Nebraska, USA, October 2016

    Google Scholar 

  12. Basu, K.: The Traveler’s Dilemma. Scientific American, pp. 90–95, June 2007

    Google Scholar 

  13. Lorini, E., Muehlenbernd, R.: The long-term benefits of following [the] fairness norms: a game-theoretic analysis. In: Proceedings 18th Conference on Principles & Practice of Multi-Agent Systems (PRIMA 2015), Lecture Notes in AI (LNAI) Series, vol. 9387, pp. 301–318. Springer (2015)

    Google Scholar 

  14. Perry, D.W.: Duopoly: How the Republicrats Control the Electoral Process. Paperback, Free Patriot Press, USA, October 2011. See also Gillespie, D.J.: Challengers to Duopoly: Why Third Parties Matter in American Two-Party Politics. University of S. Carolina Press, February 2015

    Google Scholar 

Download references

Acknowledgments

The author would like to thank his long-time research collaborator Carlos Ordonez from University of Houston, as well as his former students Phil Dasler (University of Houston) and Devin Driggs (University of Idaho) for the past joint work on Iterated Traveler’s Dilemma.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Predrag T. Tošić .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Tošić, P.T. (2019). Individual Rationality and Real-World Strategic Interactions: Understanding the Competitive-Cooperative Spectrum. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Computing. SAI 2018. Advances in Intelligent Systems and Computing, vol 858. Springer, Cham. https://doi.org/10.1007/978-3-030-01174-1_79

Download citation

Publish with us

Policies and ethics