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In previous work, I have developed an information theoretic complexitymeasure of networks. When applied to several real world food webs, there is adistinct difference in complexity between the real food web, and randomisedcontrol networks obtained by shuffling the network links. One hypothesis isthat this complexity surplus represents information captured by theevolutionary process that generated the network. In this paper, I test thisidea by applying the same complexity measure to several well-known artificiallife models that exhibit ecological networks: Tierra, EcoLab and Webworld.Contrary to what was found in real networks, the artificial life generatedfoodwebs had little information difference between itself and randomly shuffledversions.

Network Complexity of Foodwebs