P. Jean-Jacques Herings

The average tree solution for cycle-free graph games

In this paper we study cooperative games with limited cooperation possibilities, represented by an undirected cycle-free communication graph. Players in the game can cooperate if and only if they are connected in the graph. We introduce a new single-valued solution concept, the average tree solution. Our solution is characterized by component efficiency and component fairness. The interpretation of component fairness is that deleting a link between two players yields for both resulting components the same average change in payoff, where the average is taken over the players in the component. The average tree solution is always in the core of the restricted game and can be easily computed as the average of n specific marginal vectors, where n is the number of players. We also show that the average tree solution can be generated by a specific distribution of the Harsanyi dividends.

Stationary Equilibria in Stochastic Games: Structure, Selection and Computation

This paper is the first to introduce an algorithm to compute stationary equilibria in stochastic games, and shows convergence of the algorithm for almost all such games. Moreover, since in general the number of stationary equilibria is overwhelming, we pay attention to the issue of equilibrium selection. We do this by extending the linear tracing procedure to the class of stochastic games, called the stochastic tracing procedure. From a computational point of view, the class of stochastic games possesses substantial difficulties compared to normal form games. Apart from technical difficulties, there are also conceptual difficulties, for instance the question how to extend the linear tracing procedure to the environment of stochastic games.We prove that there is a generic subclass of the class of stochastic games for which the stochastic tracing procedure is a compact one-dimensionalpiecewise differentiable manifold with boundary. Furthermore, we prove that the stochastic tracing procedure generates a unique path leading from any exogenously specified prior belief, to a stationary equilibrium. A well-chosen transformation of variables is used to formulate an everywhere differentiable homotopy function, whose zeros describe the (unique) path generated by the stochastic tracing procedure. Because of differentiability we are able to follow this path using standard path-following techniques. This yields a globally convergent algorithm that is easily and robustly implemented on a computer using existing software routines. As a by-product of our results, we extend a recent result on the generic finiteness of stationary equilibria in stochastic games to oddness of equilibria.

Farsightedly Stable Networks

We propose a new concept, the pairwise farsightedly stable set, in order to predict which networks may be formed among farsighted players. A set of networks G is pairto a network outside G are deterred by the threat of ending worse off or equally well wise farsightedly stable (i) if all possible pairwise deviations from any network g G

Communication Network Formation with Link Specificity and Value Transferability

We model strategic communication network formation with (i) link specificity: link maintenance lowers specific attention and thus value (negative externality previously ignored for communication) and (ii) value transferability via indirect links for informational but not for social value (positive externality modeled uniformly before). Assuming only social value, the pairwise stable set includes many nonstandard networks under high and particular combinations of complete components under low link specificity. Allowing for social and informational value reduces this set to certain fragmented networks under high and the complete network under low link specificity. These extremes are efficient, whereas intermediate link specificity generates inefficiency.

Behavioral Effects in Individual Decisions of Network Formation: Complexity Reduces Payoff Orientation and Social Preferences

Network formation constitutes an important part of many social and economic processes, but relatively little is known about how individuals make their linking decisions in networks. This article provides an experimental investigation of behavioral effects in individual decisions of network formation. Our findings demonstrate that the inherent complexity of the network setting makes individuals’ choices systematically less payoff-guided and also strongly reduces their social orientation. Furthermore, we show that specific network complexity features aggravate the former effect. These behavioral effects have important implications for researchers and managers working in areas that involve network formation.

Rationalizability for social environments

Social environments constitute a framework in which it is possible to study how groups of agents interact in a society. The framework is general enough to analyze both non-cooperative and cooperative games. In order to remedy the shortcomings of existing solution concepts and to identify the consequences of common knowledge of rationality and farsightedness, we propose to apply extensive-form rationalizability to the framework of social environments. For us, the social environment is a primitive. On this social environment is defined a multistage game. An outcome of the social environment is socially rationalizable if and only if it is rationalizable in the multistage game. The set of socially rationalizable outcomes is shown to be non-empty for all social environments and it can be computed by an iterative reduction procedure. We introduce a definition of coalitional rationality for social environments and show that it is satisfied by social rationalizability.

A Necessary and Sufficient Condition for Non-emptiness of the Core of a Non-transferable Utility Game

It is well--known that a transferable utility game has a non-empty core if and only if it is balanced. In the class of non-transferable utility games balancedness or the more general pi-balancedness due to Billera (1970) is a sufficient, but not a necessary condition for the core to be non--empty. This paper gives a natural extension of the pi -balancedness condition that is both necessary and sufficient non--emptiness of the core.

Non-Cooperative Support for the Asymmetric Nash Bargaining Solution

We study a model of non-cooperative multilateral unanimity bargaining on a full-dimensional payoff set. The probability distribution with which the proposing player is selected in each bargaining round follows an irreducible Markov process. If a proposal is rejected, negotiations break down with an exogenous probability and the next round starts with the complementary probability. As the risk of exogenous breakdown vanishes, stationary subgame perfect equilibrium payoffs converge to the weighted Nash bargaining solution with the stationary distribution of the Markov process as the weight vector.

The Average Tree Solution for Cooperative Games with Communication Structure

We study cooperative games with communication structure, represented by an undirected graph. Players in the game are able to cooperate only if they can form a network in the graph. A single-valued solution, the average tree solution, is proposed for this class of games. The average tree solution is defined to be the average of all these payoff vectors. It is shown that if a game has a complete communication structure, then the proposed solution coincides with the Shapley value, and that if the game has a cycle-free communication structure, it is the solution proposed by Herings, van der Laan and Talman in 2008. We introduce the notion of link-convexity, under which the game is shown to have a non-empty core and the average tree solution lies in the core. In general, link-convexity is weaker than convexity. For games with a cycle-free communication structure, link-convexity is even weaker than super-additivity.

The positional power of nodes in digraphs

Many economic and social situations can be represented by a digraph. Both local and global methods to determine the strength or power of all the nodes in a digraph have been proposed in the literature. We propose a new method, where the power of a node is determined by both the number of its successors and the powers of its successors. Our method, called the positional power function, determines a full ranking of the nodes for any digraph. The positional power function can either be determined as the unique solution to a nonhomogeneous system of equations, or as the limit point of an iterative process. The solution can easily be obtained explicitly, which enables us to derive a number of interesting properties of the positional power function. We also consider the Copeland variant of the positional power function. Finally, we extend our method to the class of all weighted graphs.