Abstract
The concept of modularity appears to be crucial for many questions in the field of Artificial Life research. However, there have not been many quantitative measures for modularity that are both general and viable. In this paper we introduce a measure for modularity based on information theory. Due to the generality of the information theory formalism, this measure can be applied to various problems and models; some connections to other formalisms are presented.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Zuser, W., Biffl, S., Grechenig, T., Köhle, M.: Software Engineering. Pearson Studium, London (2001)
Dauscher, P., Uthmann, T.: On self-organizing modularization of individuals in evolutionary scenarios. In: Polani, D., Kim, J., Martinetz, T. (eds.) Proc. Fifth German Workshop on Artificial Life, Lübeck, Germany, March 18-20, Akademische Verlagsgesellschaft Aka GmbH, Berlin (2002)
Dauscher, P.: Selbstorganisierte Modularisierung von Individuen in Evolutionären Algorithmen. PhD thesis, Johannes Gutenberg-Universität Mainz (2003)
Dauscher, P., Uthmann, T.: Self-organized modularity in evolutionary algorithms. Evolutionary Computation (2005) (to appear)
Winter, S.: Zerlegung von gekoppelten Dynamischen Systemen (Decomposition of Coupled Dynamical Systems. Diploma thesis, Johannes Gutenberg-Universität Mainz (1996) (in German)
Deco, G., Schuermann, B. (eds.): Information Dynamics: Foundations and Applications. Springer, Heidelberg (2001)
Ziv, E., Middendorf, M., Wiggins, C.: An information-theoretic approach to network modularity. Physical Review E, arXiv:q-bio.QM/0411033v1 (2005) (in press)
Eriksen, K.A., Simonsen, I., Maslov, S., Sneppen, K.: Modularity and extreme edges of the internet. Phys. Rev. Lett. 90, 148701 (2003)
Magwene, P.: New tools for studying integration and modularity. Evolution 55(9), 1734–1745 (2001)
Schreiber, T.: Measuring information transfer. Phys. Rev. Lett. 85, 461–464 (2000)
Watson, R.A.: Modular interdependency in complex dynamical systems. In: Bilotta, et al. (eds.) Workshop Proceedings of the 8th International Conference on the Simulation and Synthesis of Living Systems, UNSW Australia, December 2002 (2003)
Cover, T.M., Thomas, J.A.: Elements of Information Theory. Wiley, New York (1991)
Nicholas, J.: Radcliffe. The Algebra of Genetic Algorithms. Annals of Maths and Artificial Intelligence 10(4) (1994)
Altenberg, L.: The evolution of evolvability in genetic programming. In: Kinnear, J.K.E. (ed.) Advances in Genetic Programming. MIT Press, Cambridge (1994)
Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading (1989)
Mitchell, M.: An Introduction to Genetic Algorithms. MIT Press, Cambridge (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Polani, D., Dauscher, P., Uthmann, T. (2005). On a Quantitative Measure for Modularity Based on Information Theory. In: Capcarrère, M.S., Freitas, A.A., Bentley, P.J., Johnson, C.G., Timmis, J. (eds) Advances in Artificial Life. ECAL 2005. Lecture Notes in Computer Science(), vol 3630. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553090_40
Download citation
DOI: https://doi.org/10.1007/11553090_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28848-0
Online ISBN: 978-3-540-31816-3
eBook Packages: Computer ScienceComputer Science (R0)