Near rationality and competitive equilibria in networked systems

A growing body of literature in networked systems research relies on game theory and mechanism design to model and address the potential lack of cooperation between self-interested users. Most game-theoretic models applied to system research only describe competitive equilibria in terms of pure Nash equilibria, that is, a situation where the strategy of each user is deterministic, and is her best response to the strategies of all the other users. However, the assumptions necessary for a pure Nash equilibrium to hold may be too stringent for practical systems. Using three case studies on network formation, computer security, and TCP congestion control, we outline the limits of game-theoretic models relying on Nash equilibria, and we argue that considering competitive equilibria of a more general form helps in assessing the accuracy of a game theoretic model, and can even help in reconciling predictions from game-theoretic models with empirically observed behavior.

[1]  G. Hardin,et al.  Tragedy of the Commons , 1968 .

[2]  R. Radner.  Collusive behavior in noncooperative epsilon-equilibria of oligopolies with long but finite lives , 1980 .

[3]  D. McFadden.  Econometric analysis of qualitative response models , 1984 .

[4]  Janet L. Yellen,et al.  Can Small Deviations from Rationality Make Significant Differences to Economic Equilibria , 1985 .

[5]  Philip A. Haile,et al.  On the Empirical Content of Quantal Response Equilibrium , 2003 .

[6]  Devika Subramanian,et al.  Provably Bounded Optimal Agents , 1993, IJCAI.

[7]  S. Shenker.  Making greed work in networks: a game-theoretic analysis of switch service disciplines , 1994, SIGCOMM.

[8]  R. McKelvey,et al.  Quantal Response Equilibria for Normal Form Games , 1995 .

[9]  M. Jackson,et al.  A Strategic Model of Social and Economic Networks , 1996 .

[10]  Eric J. Friedman,et al.  Learning and Implementation on the Internet , 1997 .

[11]  Michalis Faloutsos,et al.  On power-law relationships of the Internet topology , 1999, SIGCOMM '99.

[12]  Eric van Damme,et al.  Non-Cooperative Games , 2000 .

[13]  Eytan Adar,et al.  Free Riding on Gnutella , 2000, First Monday.

[14]  Mark Allman,et al.  A web server's view of the transport layer , 2000, CCRV.

[15]  Charles A. Holt,et al.  Ten Little Treasures of Game Theory and Ten Intuitive Contradictions , 2001 .

[16]  Christos H. Papadimitriou,et al.  Algorithms, Games, and the Internet , 2001, ICALP.

[17]  Raghupathy Sivakumar,et al.  Performance comparison of cellular and multi-hop wireless networks: a quantitative study , 2001, SIGMETRICS '01.

[18]  Srinivasan Seshan,et al.  Selfish behavior and stability of the internet:: a game-theoretic analysis of TCP , 2002, SIGCOMM '02.

[19]  Joan Feigenbaum,et al.  Distributed algorithmic mechanism design: recent results and future directions , 2002, DIALM '02.

[20]  P. Klemperer.  Using and Abusing Economic Theory , 2003 .

[21]  Scott Shenker,et al.  On a network creation game , 2003, PODC '03.

[22]  Stefan Savage,et al.  Inside the Slammer Worm , 2003, IEEE Secur. Priv..

[23]  B. Cohen,et al.  Incentives Build Robustness in Bit-Torrent , 2003 .

[24]  David C. Parkes,et al.  Rationality and Self-Interest in Peer to Peer Networks , 2003, IPTPS.

[25]  Jacob K. Goeree,et al.  A model of noisy introspection , 2004, Games Econ. Behav..

[26]  Ion Stoica,et al.  Characterizing selfishly constructed overlay networks , 2004, INFOCOM 2004.

[27]  Nicolas Christin,et al.  On the Cost of Participating in a Peer-to-Peer Network , 2004, IPTPS.

[28]  Michael R. Baye,et al.  Price Dispersion in the Lab and on the Internet: Theory and Evidence , 2004 .