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Dynamic Games for Analyzing Competition in the Internet and in On-Line Social Networks

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Network Games, Control, and Optimization (NETGCOOP 2016)

Abstract

The global Internet has enabled a massive access of internauts to content. At the same time it allowed individuals to use the Internet in order to distribute content. This introduced new types of competition between content over popularity, visibility, influence, reputation and user attention. The rules of these competitions are new with respect to those of traditional media, and they are determined by the way resources are allocated through network protocols (such as page rank in search engines and recommendation systems that are widely spread in social networks). In this paper we first present in the introduction an overview of some central competition issues both in the Internet as well as in other types of networks. We then describe the model of when to send content in order to maximize the exposure of the content. In the two last sections we finally describe research on two bio-inspired tools that have been used to study various competition aspects.

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Notes

  1. 1.

    Otherwise, all D + 1 players can arrive at t = 0 and remain in positions with maximal relative utility r 1 all the way up to T.

References

  1. Eitan Altman, Francesco De Pellegrini, Huijuan Wang, “Activation Games in Online Dating Platforms”, IEEE ICCW, Jun 2015, London, United Kingdom. pp.1593–1599

    Google Scholar 

  2. E. Altman and Y Hayel, “Stochastic Evolutionary Games”, Proc. of the 13th Symposium on Dynamic Games and Applications, Wroclaw, Poland, 30th June-3rd July, 2008.

    Google Scholar 

  3. E. Altman, Y. Hayel, H. Tembine and R. El-Azouzi, “Markov Decision Evolutionary Games with Expected Average Fitness”, Evolutionary Ecology Research, 11 (4):677–689, 2009

    MATH  Google Scholar 

  4. Eitan Altman, Piotr Wiecek, “Applications of Stationary Anonymous Sequential Games to Multiple Access Control in Wireless Communications”, International Workshop on Wireless Networks: Communication, Cooperation and Competition, May 2014, Hammamet, Tunisia. pp.575–578, 2014.

    Google Scholar 

  5. J. Aspnes, K. L. Chang, and A. Yampolskiy. “Inoculation strategies for victims of viruses and the sum-of-squares partition problem”. J. Comput. Syst. Sci., 72(6):1077=1093, 2006.

    Google Scholar 

  6. J Aspnes, N Rustagi, and Saia. “Worm versus alert: Who wins in a battle for control of a large-scale network?”, volume 4878 of Lecture Notes in Computer Science, Springer, 443–456. Dec 2007.

    Google Scholar 

  7. C T Bauch. “Imitation dynamics predict vaccinating behavior”. Proc. of The Royal Society, 2005.

    Google Scholar 

  8. C. T. Bauch and D. J. D. Earn. Vaccination and the theory of games. Proceedings of the National Academy of Science, 101:13391–13394, September 2004.

    Google Scholar 

  9. Alain Bensoussan, Murat Kantarcioglu and SingRu(Celine) Hoe, “A Game-Theoretical Approach for Finding Optimal Strategies in a Botnet Defense Model”, T. Alpcan, L. Buttyan, and J. Baras (Eds.): GameSec 2010, LNCS 6442, pp. 135–148, 2010.

    Google Scholar 

  10. Dominque Cardon, The digital democracy (in French), Seuil, 2010

    Google Scholar 

  11. Dominique Cardon, What do Algorithms Dream of (in French), Seuil 2015

    Google Scholar 

  12. R. Dawkins, The Selfish Gene, Oxford University Press, 1989.

    Google Scholar 

  13. Josu Doncel, Nicolas Gast, Bruno Gaujal, “Are mean-field games the limits of finite stochastic games?” The 18th Workshop on MAthematical performance Modeling and Analysis, Jun 2016, Nice, France. Performance evaluation review (PER), 2016. Available in HAL repository, https://www.archives-ouvertes.fr/hal-01321020/

  14. Josu Doncel, Nicolas Gast, Bruno Gaujal, “Mean-Field Games with Explicit Interactions”, 2016, Available in HAL repository at https://hal.inria.fr/hal-01277098.

  15. Josu Doncel, Nicolas Gast, Bruno Gaujal, “A mean-field game with explicit interactions for epidemic models”, Proceedings of the 11th Atelier of Performance Evaluation, Toulouse, 115–17 March, 2016.

    Google Scholar 

  16. Y. Hayel, S. Trajanovski, E. Altman, H. Wang, and P. V. Mieghem, “Complete game-theoretic characterization of sis epidemics protection strategies,” in Proc. 53rd IEEE Conference on Decision and Control (CDC), 2014.

    Google Scholar 

  17. Hamidou Tembine, Jean-Yves Le Boudec, Rachid El-Azouzi, Eitan Altman, “Mean field asymptotics of Markov decision evolutionary games and teams”, GameNets’ 2009.

    Google Scholar 

  18. B. Jovanovic and R.W. Rosenthal, “Anonymous Sequential Games”, J Math Economics 17:77–87,1988.

    Google Scholar 

  19. M. B. Kelley, “The Stuxnet attack on Iran’s nuclear plant was ‘far more dangerous’ than previously thought,” Online: http://www.businessinsider.com/stuxnet-was-far-more-dangerousthan-previous-thought-2013-11, accessed: June, 2014.

  20. M.H.R. Khouzani, S. Sarkar and E. Altman, “Saddle-Point Strategies in Malware Attack”, IEEE Journal on Selected Areas in Communications, Vol. 30, No. 1, January 2012.

    Google Scholar 

  21. T. G. Kurtz. Approximation of population processes, volume 36. SIAM, 1981.

    Book  Google Scholar 

  22. Avi Mandelbaum and Gennady Pats, “State-dependent stochastic networks. Part I: Approximations and applications with continuous diffusion limis,” The Annals of Applied Probability, 8(2), 569–646, 1998

    Article  MathSciNet  MATH  Google Scholar 

  23. P. Van Mieghem, J. Omic, and R. Kooij, “Virus spread in networks,” IEEE/ACM Transactions on Networking, vol. 17, no. 1, pp. 1–14, 2009.

    Article  Google Scholar 

  24. Van Mieghem, P. and R. van de Bovenkamp, 2015, “Accuracy criterion for the mean-field approximation in SIS epidemics on networks”, Physical Review E, Vol. 91, No. 3.

    Google Scholar 

  25. M.H. Manshaei, Q. Zhu, T. Alpcan, T. Basar, and J.-P. Hubaux. “Game theory meets network security and privacy”. ACM Computing Survey, 45(3):25:1–25:39, June 2013.

    Google Scholar 

  26. Guiomar Martín-Herrän and Sihem Taboubi, “Incentive Strategies for Shelf-Space Allocation in Duopolies”, in Dynamic Games: Theory and Applications, A. Haurie and G. Zaccour (edrs), Springer, pp 231–253, 2005.

    Google Scholar 

  27. W. Murrey, “The application of epidemiology to computer viruses”. Comp. Security 7:139–150, 1988.

    Article  Google Scholar 

  28. J. Omic, A. Orda, and P. V. Mieghem, “Protecting against network infections: A game theoretic perspective,” in Proceedings of INFOCOM, 2009, pp. 1485–1493.

    Google Scholar 

  29. M. Patriksson, The traffic assignment problem: models and methods, VSP, 1991.

    Google Scholar 

  30. Timothy C. Reluga, “Equilibria of an Epidemic Game with Piecewise Linear Social Distancing Cost”, Bulletin of Mathematical Biology, October 2013, Volume 75, Issue 10, pp 1961–1984.

    Google Scholar 

  31. Eitan Altman, Nahum Shimkin, “The Ordered Timeline Game: Strategic Posting Times Over a Temporally Ordered Shared Medium”, Dynamic Games and Applications, Springer Verlag, 2015, pp.1–25.

    Google Scholar 

  32. Adam Shwartz and Alan Weiss, Large Deviations for Performance Analysis, Chapman and Hall, 1995.

    MATH  Google Scholar 

  33. O. Solon, “Richard Dawkins on the internet’s hijacking of the word ‘meme”’. Wired UK. July 9, 2013.

    Google Scholar 

  34. Stojan Trajanovski, Fernando Antonio Kuipers, Yezekael Hayel, Eitan Altman, Piet Van Mieghem, “Designing virus-resistant networks: a game-formation approach”, CDC, Dec 2015, Osaka, Japan.

    Google Scholar 

  35. Piotr Wiecek, Eitan Altman, “Stationary Anonymous Sequential Games with Undiscounted Rewards”, Journal of Optimization Theory and Applications, Springer Verlag, 2015, 166 (2), pp.1–25.

    Google Scholar 

  36. Z. Xu, A. Khanafer, and T. Basar. Competition over epidemic networks: Nash and Stackelberg games. Proc. 2015 American Control Conference (ACC 2015), Chicago, IL, July 1–3, 2015, pp. 2063–2068.

    Google Scholar 

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Acknowledgements

The work of the second author was partly supported by IFCAM (Indo-French Centre for Applied Math).

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Correspondence to Eitan Altman .

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Altman, E., Jain, A., Shimkin, N., Touati, C. (2017). Dynamic Games for Analyzing Competition in the Internet and in On-Line Social Networks. In: Lasaulce, S., Jimenez, T., Solan, E. (eds) Network Games, Control, and Optimization. NETGCOOP 2016. Static & Dynamic Game Theory: Foundations & Applications. Birkhäuser, Cham. https://doi.org/10.1007/978-3-319-51034-7_2

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