Entropy of Digraphs and Infinite Networks

Chapter

Abstract

The information content of a graph G is defined in Mowshowitz (Bull Math Biophys 30:175–204, 1968) as the entropy of a finite probability scheme associated with the vertex partition determined by the automorphism group of G. This provides a quantitative measure of the symmetry structure of a graph that has been applied to problems in such diverse fields as chemistry, biology, sociology, and computer science (Mowshowitz and Mitsou, Entropy, orbits and spectra of graphs, Wiley-VCH, 2009). The measure extends naturally to directed graphs (digraphs) and can be defined for infinite graphs as well (Mowshowitz, Bull Math Biophys 30:225–240, 1968).This chapter focuses on the information content of digraphs and infinite graphs. In particular, the information content of digraph products and recursively defined infinite graphs is examined.

Keywords

Digraphs Entropy Infinite graphs Information content Networks 

Notes

Acknowledgments

Research was sponsored by the US Army Research Laboratory and the UK Ministry of Defence and was accomplished under Agreement Number W911NF-06-3-0001. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the US Army Research Laboratory, the US Government, the UK Ministry of Defence, or the UK Government. The US and UK Governments are authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon.

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Department of Computer ScienceThe City College of New York (CUNY)New YorkUSA

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