Hierarchical Coordinate Systems for Understanding Complexity and its Evolution, with Applications to Genetic Regulatory Networks

@article{EgriNagy2008HierarchicalCS,
  title={Hierarchical Coordinate Systems for Understanding Complexity and its Evolution, with Applications to Genetic Regulatory Networks},
  author={Attila Egri-Nagy and Chrystopher L. Nehaniv},
  journal={Artificial Life},
  year={2008},
  volume={14},
  pages={299-312}
}
Beyond complexity measures, sometimes it is worthwhile in addition to investigate how complexity changes structurally, especially in artificial systems where we have complete knowledge about the evolutionary process. Hierarchical decomposition is a useful way of assessing structural complexity changes of organisms modeled as automata, and we show how recently developed computational tools can be used for this purpose, by computing holonomy decompositions and holonomy complexity. To gain insight… CONTINUE READING
BETA

Citations

Publications citing this paper.
SHOWING 1-10 OF 14 CITATIONS

References

Publications referenced by this paper.
SHOWING 1-10 OF 30 REFERENCES

Formal models of understanding. http://graspermachine.sf.net

  • A. Egri-Nagy, C. L. Nehaniv
  • 2003
Highly Influential
4 Excerpts

The regulatory genome: Gene regulatory networks in development and evolution

  • E. H. Davidson
  • 2006

Algebraic theory of automata networks: An introduction

  • P. Dömösi, C. L. Nehaniv
  • 2005
1 Excerpt

Krohn - Rhodes theory and complete classes

  • P. Dömösi, C. L. Nehaniv
  • Algebraic theory of automata networks : An…
  • 2005

Similar Papers

Loading similar papers…