  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.
