Observational learning in an uncertain world
Daron Acemoglu,Munther A. Dahleh,Asuman Ozdaglar,Alireza Tahbaz-Salehi +3 more
- pp 6645-6650
Reads0
Chats0
TLDR
It is shown that information is correctly aggregated when preferences of different types are closely aligned, and even though learning is guaranteed to be incomplete ex ante, there are sample paths over which agents become certain about the underlying state of the world.Abstract:
We study a model of observational learning in social networks in the presence of uncertainty about agents' type distributions. Each individual receives a private noisy signal about a payoff-relevant state of the world, and can observe the actions of other agents who have made a decision before her. We assume that agents do not observe the signals and types of others in the society, and are also uncertain about the type distributions. We show that information is correctly aggregated when preferences of different types are closely aligned. On the other hand, if there is sufficient heterogeneity in preferences, uncertainty about type distributions leads to potential identification problems, preventing asymptotic learning. We also show that even though learning is guaranteed to be incomplete ex ante, there are sample paths over which agents become certain about the underlying state of the world.read more
Citations
More filters
Proceedings ArticleDOI
Learning over social networks via diffusion adaptation
Xiaochuan Zhao,Ali H. Sayed +1 more
TL;DR: It is shown that the diffusion algorithm converges almost surely to the true state and the superior convergence rate of the diffusion strategy over consensus-based strategies since diffusion schemes allow information to diffuse more thoroughly through the network.
Journal ArticleDOI
Social Learning Over Weakly Connected Graphs
TL;DR: It is shown that the asymmetric flow of information hinders the learning abilities of certain agents regardless of their local observations, and useful closed-form expressions are derived which can be used to motivate design problems to control it.
Journal ArticleDOI
Interplay Between Topology and Social Learning Over Weak Graphs
TL;DR: In this paper, the authors examine a distributed learning problem where the agents of a network form their beliefs about certain hypotheses of interest each agent collects streaming (private) data and updates continually its belief by means of a diffusion strategy, which blends the agent's data with the beliefs of its neighbors.
Posted Content
Interplay between Topology and Social Learning over Weak Graphs.
TL;DR: This work examines a distributed learning problem where the agents of a network form their beliefs about certain hypotheses of interest by means of a diffusion strategy and examines the feasibility of topology learning for two useful classes of problems.
Proceedings ArticleDOI
Diffusion social learning over weakly-connected graphs
TL;DR: It is shown that the asymmetric flow of information hinders the learning abilities of certain agents regardless of their local observations, and useful closed-form expressions are derived which can be used to motivate design problems to control it.
References
More filters
Journal ArticleDOI
A Simple Model of Herd Behavior
TL;DR: In this article, the authors analyze a sequential decision model in which each decision maker looks at the decisions made by previous decision makers in taking her own decision, and they show that the decision rules that are chosen by optimizing individuals will be characterized by herd behavior.
Posted Content
A Theory of Fads, Fashion, Custom, and Cultural Change as Informational Cascades
TL;DR: It is argued that localized conformity of behavior and the fragility of mass behaviors can be explained by informational cascades.
Book
Probability: Theory and Examples
TL;DR: In this paper, a comprehensive introduction to probability theory covering laws of large numbers, central limit theorem, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion is presented.
Journal ArticleDOI
A Theory of Fads, Fashion, Custom, and Cultural Change as Informational Cascades
TL;DR: In this paper, the authors argue that localized conformity of behavior and the fragility of mass behaviors can be explained by informational cascades, where an individual, having observed the actions of those ahead of him, to follow the behavior of the preceding individual without regard to his own information.