Skip to main content
SpringerLink
Log in

Comparative Efficiency of Altruism and Egoism as Voting Strategies in Stochastic Environment

  • Control in Technical Systems
  • Published:
Automation and Remote Control Aims and scope Submit manuscript

Abstract

In this paper, we study the efficiency of egoistic and altruistic strategies within the model of social dynamics determined by voting in a stochastic environment (the ViSE model) using two criteria: maximizing the average capital increment and minimizing the number of bankrupt participants. The proposals are generated stochastically; three families of the corresponding distributions are considered: normal distributions, symmetrized Pareto distributions, and Student’s t-distributions. It is found that the “pit of losses” paradox described earlier does not occur in the case of heavy-tailed distributions. The egoistic strategy better protects agents from extinction in aggressive environments than the altruistic ones, however, the efficiency of altruism is higher in more favorable environments. A comparison of altruistic strategies with each other shows that in aggressive environments, everyone should be supported to minimize extinction, while under more favorable conditions, it is more efficient to support the weakest participants. Studying the dynamics of participants’ capitals we identify situations where the two considered criteria contradict each other. At the next stage of the study, combined voting strategies and societies involving participants with selfish and altruistic strategies will be explored.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Borzenko, V.I., Lezina, Z.M., Loginov, A.K., Tsodikova, Ya.Yu., and Chebotarev, P.Yu., Strategies of Voting in Stochastic Environment: Egoism and Collectivism, Autom. Remote Control, 2006, vol. 67, no. 2, pp. 311–328.

    Article  MathSciNet  MATH  Google Scholar 

  2. Chebotarev, P.Yu., Analytical Expression of the Expected Values of Capital at Voting in the Stochastic Environment, Autom. Remote Control, 2006, vol. 67, no. 3, pp. 480–492.

    Article  MathSciNet  MATH  Google Scholar 

  3. Chebotarev, P.Yu., Loginov, A.K., Tsodikova, Ya.Yu., Lezina, Z.M., and Borzenko, V.I., Snowball of Cooperation and Snowball Communism, Proc. Fourth Int. Conf. on Control Sciences, Moscow: Inst. Probl. Upravlen., 2009, pp. 687–699.

    Google Scholar 

  4. Chebotarev, P.Yu., Loginov, A.K., Tsodikova, Ya.Yu., Lezina, Z.M., and Borzenko, V.I., Voting in a Stochastic Environment: The Case of Two Groups, Autom. Remote Control, 2011, vol. 72, no. 7, pp. 1537–1547.

    Article  MATH  Google Scholar 

  5. Chebotarev, P.Yu., Tsodikova, Ya.Yu., Loginov, A.K., and Lezina, Z.M., What Percentage of Altruists Is Needed in Society and What Should They Direct Their Efforts Towards? Second Russian Economic Congress, Suzdal, February 18–22, 2013, Moscow: New Economic Association, 2013, pp. 1–3.

    Google Scholar 

  6. Chebotarev, P.Yu., Lezina, Z.M., Loginov, A.K., and Tsodikova, Ya.Yu., The Effectiveness of Altruistic Lobbying: A Model Study, in Game Theory and Management, St. Petersburg: St. Petersburg Univ., 2013, pp. 50–53.

    Google Scholar 

  7. Chebotarev, P.Yu., Malyshev, V.A., Tsodikova, Ya.Yu., Loginov, A.K., Lezina, Z.M., and Afonkin, V.A., The Optimal Majority Threshold as a Function of the Variation Coefficient of the Environment, Autom. Remote Control, 2018, vol. 79, no. 4, pp. 725–736.

    Article  MATH  Google Scholar 

  8. Malyshev, V.A. and Chebotarev, P.Yu., On Optimal Group Claims at Voting in a Stochastic Environment, Autom. Remote Control, 2017, vol. 78, no. 6, pp. 1087–1100.

    Article  MathSciNet  MATH  Google Scholar 

  9. Mirkin, B.G., Problema gruppovogo vybora, Moscow: Nauka, 1974. Translated under the title Group Choice, Fishburn, P.C., Ed., New York: Wiley, 1979.

  10. McKelvey, R.D., Game Theoretic Models of Voting in Multidimensional Issue Spaces, in Game Theory Appl., Ichiishi, T., Neyman, A., and Tauman, Y., Eds., San Diego: Academic, 1990, pp. 317–335.

    Chapter  Google Scholar 

  11. Ordeshook, P.C., The Spatial Analysis of Elections and Committees: Four Decades of Research, in Perspectiv. Public Choice: A Handbook, Mueller, D., Ed., Cambridge, U.K.: Cambridge Univer. Press, 1997, pp. 247–270.

    Google Scholar 

  12. Hinich, M.J. and Munger, M.C., Spatial Theory, in Readings in Public Choice and Constitutional Political Economy, Rowley, C.K. and Schneider, F., Eds., New York: Springer, 2008, pp. 295–304.

    Chapter  Google Scholar 

  13. Baron, D.P. and Ferejohn, J.A., Bargaining in Legislatures, Am. Polit. Sci. Rev., 1989, vol. 83, no. 4, pp. 1181–1206.

    Article  Google Scholar 

  14. Merlo, A. and Wilson, C., A Stochastic Model of Sequential Bargaining with Complete Information, Econometrica, 1995, vol. 63, no. 2, pp. 371–399.

    Article  MathSciNet  MATH  Google Scholar 

  15. Gomes, A. and Jehiel, P., Dynamic Processes of Social and Economic Interactions: On the Persistence of Inefficiencies, J. Polit. Econom., 2005, vol. 113, pp. 626–667.

    Article  Google Scholar 

  16. Kalandrakis, T., Majority Rule Dynamics with Endogenous Status Quo, Univ. Rochester, Wallis Inst. Polit. Econom., WP46, 2007, P. 1–38.

    Google Scholar 

  17. Epple, D. and Riordan, M.H., Cooperation and Punishment under Repeated Majority Voting, Public Choice, 1987, vol. 55, no. 1–2, pp. 41–73.

    Article  Google Scholar 

  18. Cotton, C., Dynamic Legislative Bargaining with Endogenous Agenda Setting Authority, Working Paper, Department of Economics, University of Miami, 2012, SSRN paper no. 1699211. DOI: 10.2139/ssrn.1699211

    Google Scholar 

  19. Riboni, A., Committees as Substitutes for Commitment, Int. Econom. Rev., 2010, vol. 51, no. 1, pp. 213–236.

    Article  MathSciNet  Google Scholar 

  20. Dziuda, W. and Loeper, A., Dynamic Collective Choice with Endogenous Status Quo, J. Polit. Economy, 2016, vol. 124, no. 4, pp. 1148–1186.

    Article  Google Scholar 

  21. Borzenko, V.I., Lezina, Z.M., Lezina, I.V., Loginov, A.K., Tsodikova, Ya.Yu., and Chebotarev, P.Yu., A Model of Social Dynamics Determined by Collective Decisions and Random Changes in the Environment, Second Int. Conference on Control Problems, Moscow: Inst. Probl. Upravlen., 2003.

    Google Scholar 

  22. Penn, E.M., A Model of Farsighted Voting, Am. J. Polit. Sci., 2009, vol. 53, no. 1, pp. 36–54.

    Article  Google Scholar 

  23. Dziuda, W. and Loeper, A., Voting Rules in a Changing Environment, SSRN paper 2500777, 2015. DOI: 10.2139/ssrn.2500777

    Google Scholar 

  24. Eavey, C.L., Preference-Based Stability: Experiments on Cooperative Solutions to Majority Rule Games, in Collectiv. Decision-Making: Social Choice Polit. Econom., New York: Springer, 1996, pp. 149–181.

    Chapter  Google Scholar 

  25. Krishna, V. and Morgan, J., Majority Rule and Utilitarian Welfare, Am. Econom. J.: Microeconom., 2015, vol. 7, no. 4, pp. 339–375.

    Google Scholar 

  26. Compte, O. and Jehiel, P., On the Optimal Majority Rule, CEPR Discussion Paper no. DP12492, 2017.

    MATH  Google Scholar 

  27. Binmore, K. and Eguia, J.X., Bargaining with Outside Options, in State, Institutions and Democracy. Contributions of Political Economy, Schofield, N. and Caballero, G., Eds., New York: Springer, 2017, pp. 3–16.

    Chapter  Google Scholar 

  28. Hortala-Vallve, R., Qualitative Voting, J. Theoret. Polit., 2012, vol. 24, no. 4, pp. 526–554.

    Article  Google Scholar 

  29. Pareto, V., Cours d’économie politique, Geneva: Librairie Droz, 1964, vol. 1, pp. 299–345.

    Google Scholar 

  30. Rosenblatt, M., Non-Gaussian Linear Processes, in Stationar. Sequen. Random Fields, Boston: Birkhäuser, 1985, pp. 205–238.

    Chapter  Google Scholar 

  31. Mittnik, S. and Rachev, S.T., Modeling Asset Returns with Alternative Stable Distributions, Econometr. Rev., 1993, vol. 12, no. 3, pp. 261–330.

    Article  MathSciNet  MATH  Google Scholar 

  32. Grabchak, M. and Samorodnitsky, G., Do Financial Returns Have Finite or Infinite Variance? A Paradox and an Explanation, Quantit. Finance, 2010, vol. 10, no. 8, pp. 883–893.

    Article  MathSciNet  MATH  Google Scholar 

  33. Huang, X., Zhou, Y., and Zhang, R., Variable Bit Rate Video Traffic Modeling by Multiplicative Multifractal Model, J. Syst. Engineer. Electron., 2006, vol. 17, no. 1, pp. 75–79.

    Article  MATH  Google Scholar 

  34. Anabila, M.A., Skew Pareto Distributions, Master Thesis, Reno: Univ. of Nevada, 2008.

    Google Scholar 

  35. Taleb, N.N., The Black Swan: The Impact of the Highly Improbable, New York: Random House, 2007.

    Google Scholar 

  36. Taleb, N.N., Antifragile: Things That Gain from Disorder, New York: Random House, 2012.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Trapeznikov Institute of Control Sciences, Russian Academy of Sciences, Moscow, Russia

    P. Yu. Chebotarev, Ya. Yu. Tsodikov, A. K. Loginov, Z. M. Lezina, V. A. Afonkin & V. A. Malyshev

  2. Kotelnikov Institute of Radioengineering and Electronics, Russian Academy of Sciences, Moscow, Russia

    P. Yu. Chebotarev & V. A. Malyshev

  3. Moscow Institute of Physics and Technology, Moscow, Russia

    P. Yu. Chebotarev, V. A. Afonkin & V. A. Malyshev

Authors
  1. P. Yu. Chebotarev
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ya. Yu. Tsodikov
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. A. K. Loginov
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Z. M. Lezina
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. V. A. Afonkin
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. V. A. Malyshev
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to P. Yu. Chebotarev.

Additional information

Original Russian Text © P.Yu. Chebotarev, Ya.Yu. Tsodikova, A.K. Loginov, Z.M. Lezina, V.A. Afonkin, V.A. Malyshev, 2018, published in Avtomatika i Telemekhanika, 2018, No. 11, pp. 123–149.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chebotarev, P.Y., Tsodikov, Y.Y., Loginov, A.K. et al. Comparative Efficiency of Altruism and Egoism as Voting Strategies in Stochastic Environment. Autom Remote Control 79, 2052–2072 (2018). https://doi.org/10.1134/S0005117918110097

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0005117918110097

Keywords

Search

Navigation