Strategic formation of credit networks

Credit networks are an abstraction for modeling trust between agents in a network. Agents who do not directly trust each other can transact through exchange of IOUs (obligations) along a chain of trust in the network. Credit networks are robust to intrusion, can enable transactions between strangers in exchange economies, and have the liquidity to support a high rate of transactions. We study the formation of such networks when agents strategically decide how much credit to extend each other. When each agent trusts a fixed set of other agents, and transacts directly only with those it trusts, the formation game is a potential game and all Nash equilibria are social optima. Moreover, the Nash equilibria of this game are equivalent in a very strong sense: the sequences of transactions that can be supported from each equilibrium credit network are identical. When we allow transactions over longer paths, the game may not admit a Nash equilibrium, and even when it does, the price of anarchy may be unbounded. Hence, we study two special cases. First, when agents have a shared belief about the trustworthiness of each agent, the networks formed in equilibrium have a star-like structure. Though the price of anarchy is unbounded, myopic best response quickly converges to a social optimum. Similar star-like structures are found in equilibria of heuristic strategies found via simulation. In addition, we simulate a second case where agents may have varying information about each others' trustworthiness based on their distance in a social network. Empirical game analysis of these scenarios suggests that star structures arise only when defaults are relatively rare, and otherwise, credit tends to be issued over short social distances conforming to the locality of information.

[1]  Abraham Neyman,et al.  Correlated equilibrium and potential games , 1997, Int. J. Game Theory.

[2]  Michael P. Wellman,et al.  Learning payoff functions in infinite games , 2005, Machine Learning.

[3]  Ramesh Govindan,et al.  Liquidity in credit networks: a little trust goes a long way , 2011, EC '11.

[4]  David M. Pennock,et al.  Mechanism Design on Trust Networks , 2007, WINE.

[5]  Michael P. Wellman,et al.  Strategic formation of credit networks , 2012, WWW.

[6]  Krishna P. Gummadi,et al.  Ostra: Leveraging Trust to Thwart Unwanted Communication , 2008, NSDI.

[7]  Mohammad Mahdian.  Fighting censorship with algorithms , 2011, XRDS.

[8]  L. Shapley,et al.  Potential Games , 1994 .

[9]  CorboJacomo,et al.  A study of Nash equilibrium in contribution games for peer-to-peer networks , 2006 .

[10]  E. Friedman,et al.  Algorithmic Game Theory: Manipulation-Resistant Reputation Systems , 2007 .

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

[12]  Michael P. Wellman,et al.  Generalization risk minimization in empirical game models , 2009, AAMAS.

[13]  Michael P. Wellman.  Methods for Empirical Game-Theoretic Analysis , 2006, AAAI.

[14]  L. Shapley,et al.  REGULAR ARTICLEPotential Games , 1996 .

[15]  Michael P. Wellman,et al.  EGTAOnline: An Experiment Manager for Simulation-Based Game Studies , 2012, MABS.

[16]  Éva Tardos,et al.  Network Formation in the Presence of Contagious Risk , 2011, TEAC.

[17]  Sanjeev Goyal,et al.  A Noncooperative Model of Network Formation , 2000 .

[18]  M. Barnard.  Needle sharing in context: patterns of sharing among men and women injectors and HIV risks. , 1993, Addiction.

[19]  Keith W. Ross,et al.  P2P Trading in Social Networks: The Value of Staying Connected , 2010, 2010 Proceedings IEEE INFOCOM.

[20]  Krishna P. Gummadi,et al.  Canal: scaling social network-based Sybil tolerance schemes , 2012, EuroSys '12.

[21]  Michael P. Wellman,et al.  Analyzing Incentives for Protocol Compliance in Complex Domains: A Case Study of Introduction-Based Routing , 2013, ArXiv.

[22]  E. Friedman,et al.  The Social Cost of Cheap Pseudonyms , 2001 .

[23]  David C. Parkes,et al.  A study of Nash equilibrium in contribution games for peer-to-peer networks , 2006, OPSR.

[24]  M. Mobius,et al.  Trust and Social Collateral , 2007 .

[25]  M. Jackson,et al.  Social Capital and Social Quilts: Network Patterns of Favor Exchange , 2011 .

[26]  Michael P. Wellman,et al.  Scaling simulation-based game analysis through deviation-preserving reduction , 2012, AAMAS.

[27]  Denis Gillet,et al.  A Competence Bartering Platform for Learners , 2011, ICWL.

[28]  Lisa Sattenspiel,et al.  Modeling and analyzing HIV transmission: the effect of contact patterns , 1988 .

[29]  Earl T. Barr,et al.  TrustDavis: a non-exploitable online reputation system , 2005, Seventh IEEE International Conference on E-Commerce Technology (CEC'05).

[30]  Michael P. Wellman,et al.  Approximate Strategic Reasoning through Hierarchical Reduction of Large Symmetric Games , 2005, AAAI.

[31]  Martin Hoefer,et al.  Contribution Games in Networks , 2010, Algorithmica.

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

[33]  Michael P. Wellman,et al.  Methods for empirical game-theoretic analysis (extended abstract) , 2006 .