1This paper is based on some parts of my PhD thesis supervisored by Tilman Börgers at UCL. I really thanks him for his advice and support. Financial support from the Bank of Spain is gratefully acknowledged. This paper analyses a model of learning by imitation, where besides the decision maker, there is a population of individuals facing the same decision problem. We analyse a property called Absolute Expediency, which requires that the decision maker’s expected payo ¤ increases from one round to the next for every decision problem and every state of the population. We give a simple characterisation of the expediency property and show that its basic feature is proportional imitation: the change in the probability attached to the played acti...
We introduce a generalized theoretical approach to study imitation and subject it to rigorous experi...
The paper considers a model of imitation in the context of Cournot oligopoly. Purely imitative behav...
Many existing imitation learning datasets are collected from multiple demonstrators, each with diffe...
This thesis studies a population of agents facing repeatedly the same decision problem. Each agent k...
Cataloged from PDF version of article.This paper introduces a learning algorithm that allows for imi...
In an experimental standard Cournot oligopoly we test the importance of models of behaviour characte...
A significant increase in the probability of an action resulting from observing that action performe...
In consectutive rounds, each agent in a finite population chooses an action, is randomly matched, ob...
The experiment described in this paper analyzes imitation in an individ-ual learning context. It sup...
We model a learning dynamic in which players imitate and innovate. Of interest is to question wheth...
Three results emerge from a simple experiment on imitation. First, I find behavior which strongly su...
We study a boundedly rational model of imitation when payoff distributions of actions differ across ...
Abstract. Reinforcement learning techniques are increasingly being used to solve dicult problems in ...
We study a boundedly rational model of imitation when payoff distributions of actions differ across ...
We show that for many classes of symmetric two-player games, the simple decision rule "imitate-the-b...
We introduce a generalized theoretical approach to study imitation and subject it to rigorous experi...
The paper considers a model of imitation in the context of Cournot oligopoly. Purely imitative behav...
Many existing imitation learning datasets are collected from multiple demonstrators, each with diffe...
This thesis studies a population of agents facing repeatedly the same decision problem. Each agent k...
Cataloged from PDF version of article.This paper introduces a learning algorithm that allows for imi...
In an experimental standard Cournot oligopoly we test the importance of models of behaviour characte...
A significant increase in the probability of an action resulting from observing that action performe...
In consectutive rounds, each agent in a finite population chooses an action, is randomly matched, ob...
The experiment described in this paper analyzes imitation in an individ-ual learning context. It sup...
We model a learning dynamic in which players imitate and innovate. Of interest is to question wheth...
Three results emerge from a simple experiment on imitation. First, I find behavior which strongly su...
We study a boundedly rational model of imitation when payoff distributions of actions differ across ...
Abstract. Reinforcement learning techniques are increasingly being used to solve dicult problems in ...
We study a boundedly rational model of imitation when payoff distributions of actions differ across ...
We show that for many classes of symmetric two-player games, the simple decision rule "imitate-the-b...
We introduce a generalized theoretical approach to study imitation and subject it to rigorous experi...
The paper considers a model of imitation in the context of Cournot oligopoly. Purely imitative behav...
Many existing imitation learning datasets are collected from multiple demonstrators, each with diffe...