3 papers
econ.GN2023
Consensus and Disagreement: Information Aggregation under (not so) Naive Learning
Abhijit Banerjee, Olivier Compte
We explore a model of non-Bayesian information aggregation in networks. Agents non-cooperatively choose among Friedkin-Johnsen type aggregation rules to maximize payoffs. The DeGro…
econ.GN2023
Endogenous Barriers to Learning
Olivier Compte
Building on the idea that lack of experience is a source of errors but that experience should reduce them, we model agents' behavior using a stochastic choice model (logit quantal…
econ.TH2023
Learned Collusion
Olivier Compte
Q-learning can be described as an all-purpose automaton that provides estimates (Q-values) of the continuation values associated with each available action and follows the naive po…