In this note, we consider repeated play of a finite game using learning rules whose period-by-period behavior probabilities or empirical distributions converge to some notion of equilibria of the stage game. Our primary focus is on uncoupled and com-pletely uncoupled learning rules. While the former relies on players being aware of only their own payoff functions and able to monitor the action taken by the others, the latter assumes that players only know their own past realized payoffs. We highlight the border between possible and impossible results using these rules. We also overview several uncoupled and completely uncoupled learning rules, most of which leverage notions of regret as the solution concept to seek payoff-improving action p...
Melioration learning is an empirically well-grounded model of reinforcement learning. By means of co...
This paper explores the extent to which people learn in repeated games without feedback, and the ext...
International audienceIn game-theoretic learning, several agents are simultaneously following their ...
A learning rule is uncoupled if a player does not condition his strategy on the opponent's payoffs. ...
[This item is a preserved copy. To view the original, visit http://econtheory.org/] A learning rule ...
∗The authors thank Andrew Felton, Ben Klemens, and several anonymous referees for constructive comme...
A learning rule is uncoupled if a player does not condition his strategy on the opponent’s payoffs. ...
In imperfect-information games, a common assumption is that players can perfectly model the strategi...
Abstract: We consider boundedly rational learning processes in which players have a priori limited s...
The paper studies infinite repetition of finite strategic form games. Players use a learning behavio...
Do boundedly rational players learn to choose equilibrium strategies as they play a game repeatedly?...
This paper presents a new, probabilistic model of learning in games which investigates the often sta...
This paper tests a learning-based model of strategic teaching in repeated games with incomplete info...
It is shown by example that learning rules of the fictitious play type fail to converge in certain k...
Consider a finite stage game G that is repeated infinitely often. At each time, the players have hyp...
Melioration learning is an empirically well-grounded model of reinforcement learning. By means of co...
This paper explores the extent to which people learn in repeated games without feedback, and the ext...
International audienceIn game-theoretic learning, several agents are simultaneously following their ...
A learning rule is uncoupled if a player does not condition his strategy on the opponent's payoffs. ...
[This item is a preserved copy. To view the original, visit http://econtheory.org/] A learning rule ...
∗The authors thank Andrew Felton, Ben Klemens, and several anonymous referees for constructive comme...
A learning rule is uncoupled if a player does not condition his strategy on the opponent’s payoffs. ...
In imperfect-information games, a common assumption is that players can perfectly model the strategi...
Abstract: We consider boundedly rational learning processes in which players have a priori limited s...
The paper studies infinite repetition of finite strategic form games. Players use a learning behavio...
Do boundedly rational players learn to choose equilibrium strategies as they play a game repeatedly?...
This paper presents a new, probabilistic model of learning in games which investigates the often sta...
This paper tests a learning-based model of strategic teaching in repeated games with incomplete info...
It is shown by example that learning rules of the fictitious play type fail to converge in certain k...
Consider a finite stage game G that is repeated infinitely often. At each time, the players have hyp...
Melioration learning is an empirically well-grounded model of reinforcement learning. By means of co...
This paper explores the extent to which people learn in repeated games without feedback, and the ext...
International audienceIn game-theoretic learning, several agents are simultaneously following their ...