A simple Bayesian heuristic for social learning and groupthink

نویسندگان

  • Gilat Levy
  • Ronny Razin
چکیده

In this paper we analyze a simple Bayesian heuristic for learning from others’posteriors and show its applicability to communication in groups and in social networks. The heuristic corresponds to rational Bayesian updating when individuals have conditionally independent information. When agents suffer from corelation neglect they also use the Heuristic. We show that communication in groups can lead to more polarized or less polarized beliefs for the group compared with those of the individuals. Applying the heuristic for social learning in networks, we show how consensus is in itself dynamic, and can shift as a result of repeated communication.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Social and Evolutionary Rationality

We live in a social world. Most other animals do too. The social world affords many opportunities and challenges for decision making, from the benefi ts of collective cognition and cooperation to the costs of groupthink and cut-throat competition. Some social situations appear, at least at the moment, to be uniquely human. For instance, morality in humans has been studied for millennia, with do...

متن کامل

2. the Sequential Social Learning Model

Social ties convey information through observations of others’ decisions as well as through conversations and the sharing of opinions. The resulting information flows play a role in a range of phenomena, including job search (Montgomery 1991), financial planning (Duflo and Saez 2003), product choice (Trusov et al. 2009), and voting (Beck et al. 2002). Understanding how individuals use informati...

متن کامل

Learning in Social Networks

Social ties convey information through observations of others’ decisions as well as through conversations and the sharing of opinions. The resulting information flows play a role in a range of phenomena, including job search (Montgomery 1991), financial planning (Duflo and Saez 2003), product choice (Trusov et al. 2009), and voting (Beck et al. 2002). Understanding how individuals use informati...

متن کامل

Learning Bayesian Network Structure Using Genetic Algorithm with Consideration of the Node Ordering via Principal Component Analysis

‎The most challenging task in dealing with Bayesian networks is learning their structure‎. ‎Two classical approaches are often used for learning Bayesian network structure;‎ ‎Constraint-Based method and Score-and-Search-Based one‎. ‎But neither the first nor the second one are completely satisfactory‎. ‎Therefore the heuristic search such as Genetic Alg...

متن کامل

An Improved Admissible Heuristic for Learning Optimal Bayesian Networks

Recently two search algorithms, A* and breadthfirst branch and bound (BFBnB), were developed based on a simple admissible heuristic for learning Bayesian network structures that optimize a scoring function. The heuristic represents a relaxation of the learning problem such that each variable chooses optimal parents independently. As a result, the heuristic may contain many directed cycles and r...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014