IDEAS home Printed from https://ideas.repec.org/a/eee/thpobi/v136y2020icp31-40.html
   My bibliography  Save this article

Kleptoparasitic interactions modeling varying owner and intruder hunger awareness

Author

Listed:
  • Chowdhury, Noble
  • Kentiba, Kirubel
  • Mirajkar, Yashwant
  • Nasseri, Mana
  • Rychtář, Jan
  • Taylor, Dewey

Abstract

We consider a game theoretical model of kleptoparasitic interaction between two individuals, the Owner and the Intruder. The Owner is in possession of a resource and must decide whether to defend the resource against the Intruder or flee. If the Owner defends, the Intruder must decide whether to fight with the Owner or flee. The outcome of the fight depends on the hunger of the individuals, the hungrier the individual is, the more likely they are to win the fight. We consider three scenarios: (a) both individuals know their own and their opponent’s hunger, (b) individuals only know their own hunger but not that of their opponent, and (c) individuals do not know their own nor the opponent’s hunger levels. We determine Nash equilibrium strategies in each scenario. We conclude that Owner is generally willing to defend more often than the Intruder is willing to attack. Also, the Intruder’s payoff is largest in the full information case; but the Owner may benefit in the no information or partial information cases when the cost of the fight is neither too large nor too small.

Suggested Citation

  • Chowdhury, Noble & Kentiba, Kirubel & Mirajkar, Yashwant & Nasseri, Mana & Rychtář, Jan & Taylor, Dewey, 2020. "Kleptoparasitic interactions modeling varying owner and intruder hunger awareness," Theoretical Population Biology, Elsevier, vol. 136(C), pages 31-40.
    • Handle: RePEc:eee:thpobi:v:136:y:2020:i:c:p:31-40
    DOI: 10.1016/j.tpb.2020.11.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040580920300708
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tpb.2020.11.002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fre´de´rique Dubois & Luc-Alain Giraldeau & James W. A. Grant, 2003. "Resource defense in a group-foraging context," Behavioral Ecology, International Society for Behavioral Ecology, vol. 14(1), pages 2-9, January.
    2. Alexandre V. Palaoro & Mark Briffa, 2017. "Weaponry and defenses in fighting animals: how allometry can alter predictions from contest theory," Behavioral Ecology, International Society for Behavioral Ecology, vol. 28(1), pages 328-336.
    3. Ross Cressman, 2003. "Evolutionary Dynamics and Extensive Form Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262033054, April.
    4. Argasinski, K. & Broom, M., 2013. "The nest site lottery: How selectively neutral density dependent growth suppression induces frequency dependent selection," Theoretical Population Biology, Elsevier, vol. 90(C), pages 82-90.
    5. Varga, Tamás & Garay, József & Rychtář, Jan & Broom, Mark, 2020. "A temporal model of territorial defence with antagonistic interactions," Theoretical Population Biology, Elsevier, vol. 134(C), pages 15-35.
    6. M. Broom & G. D. Ruxton, 2003. "Evolutionarily stable kleptoparasitism: consequences of different prey types," Behavioral Ecology, International Society for Behavioral Ecology, vol. 14(1), pages 23-33, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ozgur Aydogmus & Erkan Gürpinar, 2022. "Science, Technology and Institutional Change in Knowledge Production: An Evolutionary Game Theoretic Framework," Dynamic Games and Applications, Springer, vol. 12(4), pages 1163-1188, December.
    2. Szabó, György & Borsos, István & Szombati, Edit, 2019. "Games, graphs and Kirchhoff laws," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 416-423.
    3. Christian Hilbe & Moshe Hoffman & Martin A. Nowak, 2015. "Cooperate without Looking in a Non-Repeated Game," Games, MDPI, vol. 6(4), pages 1-15, September.
    4. Takuya Sekiguchi, 2023. "Fixation Probabilities of Strategies for Trimatrix Games and Their Applications to Triadic Conflict," Dynamic Games and Applications, Springer, vol. 13(3), pages 1005-1033, September.
    5. Sandholm, William H. & Izquierdo, Segismundo S. & Izquierdo, Luis R., 2019. "Best experienced payoff dynamics and cooperation in the Centipede game," Theoretical Economics, Econometric Society, vol. 14(4), November.
    6. Anirban Ghatak & K. Mallikarjuna Rao & A. Shaiju, 2012. "Evolutionary Stability Against Multiple Mutations," Dynamic Games and Applications, Springer, vol. 2(4), pages 376-384, December.
    7. Lenzo, Justin & Sarver, Todd, 2006. "Correlated equilibrium in evolutionary models with subpopulations," Games and Economic Behavior, Elsevier, vol. 56(2), pages 271-284, August.
    8. Patrick Kane & Kevin J S Zollman, 2015. "An Evolutionary Comparison of the Handicap Principle and Hybrid Equilibrium Theories of Signaling," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-14, September.
    9. Aradhana Narang & A. J. Shaiju, 2019. "Evolutionary Stability of Polymorphic Profiles in Asymmetric Games," Dynamic Games and Applications, Springer, vol. 9(4), pages 1126-1142, December.
    10. Fabio Lamantia & Mario Pezzino & Fabio Tramontana, 2017. "Tax Evasion, Intrinsic Motivation, and the Evolutionary Effects of Tax Reforms," Economics Discussion Paper Series 1707, Economics, The University of Manchester.
    11. Han, The Anh & Traulsen, Arne & Gokhale, Chaitanya S., 2012. "On equilibrium properties of evolutionary multi-player games with random payoff matrices," Theoretical Population Biology, Elsevier, vol. 81(4), pages 264-272.
    12. Zibo Xu, 2013. "The instability of backward induction in evolutionary dynamics," Discussion Paper Series dp633, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    13. Bezin, Emeline & Ponthière, Gregory, 2019. "The tragedy of the commons and socialization: Theory and policy," Journal of Environmental Economics and Management, Elsevier, vol. 98(C).
    14. Cressman, Ross & Hofbauer, Josef & Riedel, Frank, 2005. "Stability of the Replicator Equation for a Single-Species with a Multi-Dimensional Continuous Trait Space," Bonn Econ Discussion Papers 12/2005, University of Bonn, Bonn Graduate School of Economics (BGSE).
    15. Elijah D. Bolluyt & Cristina Comaniciu, 2019. "Dynamic Influence on Replicator Evolution for the Propagation of Competing Technologies," Papers 1911.03000, arXiv.org.
    16. Dieter Balkenborg & Josef Hofbauer & Christoph Kuzmics, 2009. "The Refined Best-Response Correspondence and Backward Induction," Levine's Working Paper Archive 814577000000000248, David K. Levine.
    17. Jacek Miȩkisz & Sergiusz Wesołowski, 2011. "Stochasticity and Time Delays in Evolutionary Games," Dynamic Games and Applications, Springer, vol. 1(3), pages 440-448, September.
    18. Takuya Sekiguchi & Hisashi Ohtsuki, 2017. "Fixation Probabilities of Strategies for Bimatrix Games in Finite Populations," Dynamic Games and Applications, Springer, vol. 7(1), pages 93-111, March.
    19. Anufriev, Mikhail & Kopányi, Dávid & Tuinstra, Jan, 2013. "Learning cycles in Bertrand competition with differentiated commodities and competing learning rules," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2562-2581.
    20. Pawlowitsch, Christina, 2008. "Why evolution does not always lead to an optimal signaling system," Games and Economic Behavior, Elsevier, vol. 63(1), pages 203-226, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:thpobi:v:136:y:2020:i:c:p:31-40. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/intelligence .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.