It is known that a player in a noncooperative game can benefit by publicly re- stricting their possible moves before start of play. We show that, more generally, a player may benefit by publicly committing to pay an external party an amount that is contingent on the game's outcome. We explore...

We extend a recently introduced approach to the positive problem of game theory, Predictive Game Theory (PGT Wolpert (2008). In PGT, modeling a game results in a probability distribution over possible behavior profiles. This contrasts with the conventional approach where modeling a game results...

Conventionally, game theory predicts that the mixed strategy profile of players in a noncooperative game will satisfy some equilibrium concept. Relative probabil- ities of the strategy profiles satisfying the concept are unspecified, and all strategies not satisfying it are implicitly assigned...

We examine the potential for simple auction mechanisms to efficiently allocate arrival and departure slots during Ground Delay Programs (GDPs). The analysis is conducted using a new approach to predicting strategic behavior called Predictive Game Theory (PGT). The difference between PGT and the...

This paper examines a general model of sales contests in which agents have heterogeneous attitudes toward risk. It shows that agents that are less risk averse have a higher probability of success. A corollary to this result shows that when absolute risk aversion is decreasing in wealth,...

We consider the problem of designing (perhaps massively distributed) collectives of computational processes to maximize a provided "world utility" function. We consider this problem when the behavior of each process in the collective can be cast as striving to maximize its own payoff utility...

Recent work has shown how information theory extends conventional full-rationality game theory to allow bounded rational agents. The associated mathematical framework can be used to solve distributed optimization and control problems. This is done by translating the distributed problem into an...

Part I: Bayes Estimators and the Shannon Entropy. <p> This paper is the first of two on the problem of estimation a function of a probability distribution from a finite set of samples of that distribution. In this paper a Bayerian analysis of this problem is presented, the optimal properties of the...</p>

For systems usually characterized as complex/living/intelligent, the spatio-temporal patterns exhibited on different scales differ markedly from one another. (E.g., the biomass distribution of a human body looks very different depending on the spatial scale at which one examines that biomass.)...

The ``evidence'' procedure for setting hyperparameters is essentially the same as the techniques of ML-II and generalized maximum likelihood. Unlike those older techniques however, the evidence procedure has been justified (and used) as an approximation to the hierarchical Bayesian calculation....