Three alternative (?) stories on the late 20th-century rise of game theory

The paper presents three different reconstructions of the 1980s boom of game theory and its rise to the present status of indispensable tool-box for modern economics. The first story focuses on the Nash refinements literature and on the development of Bayesian games. The second emphasizes the role of antitrust case law, and in particular of the rehabilitation, via game theory, of some traditional antitrust prohibitions and limitations which had been challenged by the Chicago approach. The third story centers on the wealth of issues classifiable under the general headline of "mechanism design" and on the game theoretical tools and methods which have been applied to tackle them. The bottom lines are, first, that the three stories need not be viewed as conflicting, but rather as complementary, and, second, that in all stories a central role has been played by John Harsanyi and Bayesian decision theory.game theory; mechanism design; refinements of Nash equilibrium; antitrust law; John Harsanyi

Sequential Two-Player Games with Ambiguity

If players' beliefs are strictly non-additive, the Dempster-Shafer updating rule can be used to define beliefs off the equilibrium path. We define an equilibrium concept in sequential two-person games where players update their beliefs with the Dempster-Shafer updating rule. We show that in the limit as uncertainty tends to zero, our equilibrium approximates Bayesian Nash equilibrium by imposing context-dependent constraints on beliefs under uncertainty.

A General Class of Throughput Optimal Routing Policies in Multi-hop Wireless Networks

This paper considers the problem of throughput optimal routing/scheduling in a multi-hop constrained queueing network with random connectivity whose special case includes opportunistic multi-hop wireless networks and input-queued switch fabrics. The main challenge in the design of throughput optimal routing policies is closely related to identifying appropriate and universal Lyapunov functions with negative expected drift. The few well-known throughput optimal policies in the literature are constructed using simple quadratic or exponential Lyapunov functions of the queue backlogs and as such they seek to balance the queue backlogs across network independent of the topology. By considering a class of continuous, differentiable, and piece-wise quadratic Lyapunov functions, this paper provides a large class of throughput optimal routing policies. The proposed class of Lyapunov functions allow for the routing policy to control the traffic along short paths for a large portion of state-space while ensuring a negative expected drift. This structure enables the design of a large class of routing policies. In particular, and in addition to recovering the throughput optimality of the well known backpressure routing policy, an opportunistic routing policy with congestion diversity is proved to be throughput optimal.Comment: 31 pages (one column), 8 figures, (revision submitted to IEEE Transactions on Information Theory

Selecting a pooling equilibrium in a signaling game with a bounded set of signals

In this paper, we study a general class of monotone signaling games, in which the support of the signal is limited or the cost of the signal is sufficiently low and as a result, there are multiple pooling equilibria. In those games, when we relax the usual single-crossing condition, the typical restrictions on the out-of-equilibrium beliefs suggested by previous literature cannot discard any of the equilibria obtained. For this reason, we develop a new refinement called the most profitable deviator, which will be useful to select a unique equilibrium in those games. Additionally, when the standard single-crossing condition is satisfied, our criterion also chooses a unique equilibrium, which is the same as that selected by previous literature.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech