On the Internet it is easy for someone to obtain a new identity. This introduces opportunities to misbehave without paying reputational consequences. A large degree of cooperation can still emerge, through a convention in which newcomers "pay their dues" by accepting poor treatment from players...

In this paper we study consistency in the context of additive cost sharing mechanisms. We contrast an extremely weak notion of consistency with the standard definition, which we denote strong consistency. First we show that many well known CSMs are consistent in both senses: Aumann-Shapley,...

In this paper we study a large class of non-atomic games arising from interactions on the Internet, such as many users sharing a network link, researchers accessing a database or web server, subscribers to a network services provider trying to gain access to the modem pool and many more. We...

We provide several new characterizations of well known cost sharing methods (CSMs) as maxima of linear (or convex) functionals. For the Shapley-Shubik method the characterization has an interpretation in terms of randomly ordered agents choosing their most preferred CSM, while the...

We consider the social norms of repeated matching games in the presence of finite probability trembles and show that such norms must be subgame perfect along the equilibrium path but need not be subgame perfect off the equilibrium path. This is consistent with the well known experimental results...

This paper describes the results of simulation experiments performed on a suite of learning algorithms. We focus on games in network contexts. These are contexts in which (1) agents have very limited information about the game; users do not know their own (or any other agent's) payoff function,...

In this paper we develop a unified framework for the study of additive cost sharing methods. We show that any additive cost sharing method satisfying the dummy axiom can be generated by a (possibly infinite) convex combination of path generated methods. We also show that the set of scale...