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Information dynamics in small-world Boolean networks.

Joseph T Lizier¹, Siddharth Pritam, Mikhail Prokopenko

¹CSIRO Information and Communications Technology Centre, Australia. lizier@mis.mpg.de

Artificial Life

|July 19, 2011

Summary

This summary is machine-generated.

Small-world networks excel at both storing and transferring information. This balance, found near their characteristic regime, explains their prevalence in complex systems science.

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Area of Science:

Complex Systems Science
Network Science
Computational Neuroscience

Background:

Small-world networks are prevalent in nature and hypothesized to efficiently store and transfer information.
Understanding the computational capabilities of different network topologies is crucial for complex systems science.

Purpose of the Study:

To quantitatively investigate the information storage and transfer capabilities of small-world networks.
To compare small-world networks against ordered and random network topologies.

Main Methods:

Ensemble investigation of network dynamics using random Boolean functions on nodes.
Analysis of information storage and transfer across different dynamical phases (ordered vs. chaotic).
Comparison of network performance across ordered, random, and small-world topologies.

Main Results:

Ordered dynamics and low-randomness topologies favor information storage.
Chaotic dynamics and high-randomness topologies favor information transfer.
Small-world networks exhibit a balance between information storage and transfer, particularly near their characteristic regime.

Conclusions:

Small-world networks possess a unique propensity to balance information storage and transfer capacities.
This balanced capacity provides quantitative evidence for their prevalence in natural systems.
The findings offer insights into the functional advantages of small-world architectures in complex systems.