Network formation by reinforcement learning: the long and medium run
Probability
2007-05-23 v1
Abstract
We investigate a simple stochastic model of social network formation by the process of reinforcement learning with discounting of the past. In the limit, for any value of the discounting parameter, small, stable cliques are formed. However, the time it takes to reach the limiting state in which cliques have formed is very sensitive to the discounting parameter. Depending on this value, the limiting result may or may not be a good predictor for realistic observation times.
Keywords
Cite
@article{arxiv.math/0404106,
title = {Network formation by reinforcement learning: the long and medium run},
author = {Robin Pemantle and Brian Skyrms},
journal= {arXiv preprint arXiv:math/0404106},
year = {2007}
}
Comments
14 pages