Next Article in Journal
Quantifying Synergistic Information Using Intermediate Stochastic Variables
Previous Article in Journal
Breakdown Point of Robust Support Vector Machines
Article Menu
Issue 2 (February) cover image

Export Article

Open AccessArticle
Entropy 2017, 19(2), 82; doi:10.3390/e19020082

The More You Know, the More You Can Grow: An Information Theoretic Approach to Growth in the Information Age

Department of Communication, University of California, Davis, Kerr Hall 369, Davis, CA 95616, USA
Academic Editor: Raúl Alcaraz Martínez
Received: 13 December 2016 / Revised: 10 February 2017 / Accepted: 13 February 2017 / Published: 22 February 2017
(This article belongs to the Section Information Theory)
View Full-Text   |   Download PDF [2428 KB, uploaded 22 February 2017]   |  

Abstract

In our information age, information alone has become a driver of social growth. Information is the fuel of “big data” companies, and the decision-making compass of policy makers. Can we quantify how much information leads to how much social growth potential? Information theory is used to show that information (in bits) is effectively a quantifiable ingredient of growth. The article presents a single equation that allows both to describe hands-off natural selection of evolving populations and to optimize population fitness in uncertain environments through intervention. The setup analyzes the communication channel between the growing population and its uncertain environment. The role of information in population growth can be thought of as the optimization of information flow over this (more or less) noisy channel. Optimized growth implies that the population absorbs all communicated environmental structure during evolutionary updating (measured by their mutual information). This is achieved by endogenously adjusting the population structure to the exogenous environmental pattern (through bet-hedging/portfolio management). The setup can be applied to decompose the growth of any discrete population in stationary, stochastic environments (economic, cultural, or biological). Two empirical examples from the information economy reveal inherent trade-offs among the involved information quantities during growth optimization. View Full-Text
Keywords: information theory; natural selection; replicator dynamics; bet hedging; evolutionary economics; portfolio theory; entropy; Kelly criterion information theory; natural selection; replicator dynamics; bet hedging; evolutionary economics; portfolio theory; entropy; Kelly criterion
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary material

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Hilbert, M. The More You Know, the More You Can Grow: An Information Theoretic Approach to Growth in the Information Age. Entropy 2017, 19, 82.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top