Year: 2014
Type: preprint
Abstract: We describe a Bayesian model for social learning of a random variable in which agents might observe each other over a directed network. The outcomes produced are compared to those from a model in which observations occur randomly over a complete graph. In both cases we observe a nontrivial level of observation which maximizes learning, though individuals have strong incentive to defect from the societal optimum. The implications of such competition over information commons are discussed.
Source: arXiv (Cornell University)
Author: Palasek, Stan
Language: English
Topic: Game Theory and Applications
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2396486301