Nonlinear Sciences – Adaptation and Self-Organizing Systems
Scientific paper
2010-08-23
in Proceedings of Artficial Life XII, Fellerman et al. (eds), (MIT Press) p337-343 (2010)
Nonlinear Sciences
Adaptation and Self-Organizing Systems
Scientific paper
In previous work, I have developed an information theoretic complexity measure of networks. When applied to several real world food webs, there is a distinct difference in complexity between the real food web, and randomised control networks obtained by shuffling the network links. One hypothesis is that this complexity surplus represents information captured by the evolutionary process that generated the network. In this paper, I test this idea by applying the same complexity measure to several well-known artificial life models that exhibit ecological networks: Tierra, EcoLab and Webworld. Contrary to what was found in real networks, the artificial life generated foodwebs had little information difference between itself and randomly shuffled versions.
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