We formulate a dynamic learning-and-adjustment model of a market in which sellers choose signals that potentially reveal their types. If the dynamic process selects a unique limiting outcome, then that outcome must be an undefeated equilibrium; though to be undefeated does not suffice to be the...

We define a generalized state-space model with interactive unawareness and probabilistic beliefs. Such models are desirable for many potential applications of asymmetric unawareness. We develop Bayesian games with unawareness, define equilibrium, and prove existence. We show how equilibria are...

Heifetz, Meier and Schipper (2005) introduced a generalized state-space model that allows for non-trivial unawareness among several individuals and strong properties of knowledge. We show that this generalized state-space model arises naturally if states consist of maximally consistent sets of...

The standard state-spaces of asymmetric information preclude non- trivial forms of unawareness (Dekel, Lipman and Rustichini, 1998). We introduce a generalized state-space model that allows for non-trivial unawareness among several individuals, and which satisfies strong properties of knowledge...

Zwei Experimente mit Entscheidungstrdgern aus der Praxis des Finanzmarkts sind durchgefuehrt worden, um die Frage zu klaeren, ob es Umstände gibt, unter denen der Fluch des Gewinners auch Kapitalmarktprofis gefdhrdet. Die Antwort ist ein klares "Ja". Der Fluch des Gewinners schlug nicht nur im...

We address the scheduling problem of reordering an existing queue into its efficient order through trade. To that end, we consider individually rational and balanced budget direct and indirect mechanisms. We show that this class of mechanisms allows us to form efficient queues provided that...

We consider the situation in which individuals in a finite population must repeatedly choose an action yielding an uncertain payoff. Between choices, each individual may observe the performance of one other individual. We search for rules of behavior with limited memory that increase expected...

Individuals repeatedly face a multi-decision task with unknown payoff distributions. They have minimal memory and update their strategy by observing previous play (and not strategy) of someone else. We select behavior rules that increase average payoffs as often as possible in a large population...

We analyze the evolution of behavioral rules for learning how to play a two-armed bandit. Individuals have no information about the underlying pay-off distributions and have limited memory about their own past experience. Instead they must rely on information obtained trough observing the...

The effect that exogenous mistakes, made by players choosing their strategies, have on the dynamic stability for the replicator dynamic is analyzed for both asymmetric and symmetric normal form games. Through these perturbed games, the dynamic solution concept of limit asymptotic stability is...