Add to ORKGThis paper studies learning in monotone Bayesian games with one-dimensional types and finitely many actions. Players switch between actions at a set of thresholds. A learning algorithm under which players adjust their strategies in the direction of better ones using payoffs received at similar signals to their current thresholds is examined. Convergence to equilibrium is shown in the case of supermodular games and potential games.</p
We study learning in Bayesian games (or games with differentialinformation) with an arbitrary number...
A monotone game is an extensive-form game with complete information, simultaneous moves and an irrev...
This paper defines regular and weakly regular equilibria for monotone Bayesian games with one-dimens...
This paper considers a simple adaptive learning rule in Bayesian games where players employ threshol...
This paper considers a simple adaptive learning rule in Bayesian games where players employ threshol...
We consider multi-agent decision making where each agent's cost function depends on all agents' stra...
In infinitely repeated games, Nachbar (1997, 2005) has shown that Bayesian learning of a restricted ...
This paper continues the study of Bayesian learning processes for general finite-player, finite-str...
We generalize results of earlier work on learning in Bayesian games by allowing players to make deci...
AbstractWe deal with a special class of games against nature which correspond to subsymbolic learnin...
We generalize results of earlier work on learning in Bayesian games by allowing players to make deci...
Abstract In this paper I will give an example of a population game and of a locally improving stocha...
This paper studies the asymptotic behavior of Bayesian learning processes for general finite-player...
This study clarifies the conditions under which learning in games produces convergence to Nash equil...
We study learning in Bayesian games (or games with differential information) with an arbitrary numbe...
We study learning in Bayesian games (or games with differentialinformation) with an arbitrary number...
A monotone game is an extensive-form game with complete information, simultaneous moves and an irrev...
This paper defines regular and weakly regular equilibria for monotone Bayesian games with one-dimens...
This paper considers a simple adaptive learning rule in Bayesian games where players employ threshol...
This paper considers a simple adaptive learning rule in Bayesian games where players employ threshol...
We consider multi-agent decision making where each agent's cost function depends on all agents' stra...
In infinitely repeated games, Nachbar (1997, 2005) has shown that Bayesian learning of a restricted ...
This paper continues the study of Bayesian learning processes for general finite-player, finite-str...
We generalize results of earlier work on learning in Bayesian games by allowing players to make deci...
AbstractWe deal with a special class of games against nature which correspond to subsymbolic learnin...
We generalize results of earlier work on learning in Bayesian games by allowing players to make deci...
Abstract In this paper I will give an example of a population game and of a locally improving stocha...
This paper studies the asymptotic behavior of Bayesian learning processes for general finite-player...
This study clarifies the conditions under which learning in games produces convergence to Nash equil...
We study learning in Bayesian games (or games with differential information) with an arbitrary numbe...
We study learning in Bayesian games (or games with differentialinformation) with an arbitrary number...
A monotone game is an extensive-form game with complete information, simultaneous moves and an irrev...
This paper defines regular and weakly regular equilibria for monotone Bayesian games with one-dimens...