Distributed mining of the Internet for novel news: evolutionary community of news foragers

We populated a huge scale-free portion of Internet environment with news foragers. They evolved by a simple internal selective algorithm: selection concerned the memory components, being finite in size and containing the list of most promising supplies. Foragers received reward for locating not yet found news and used value estimation. Foragers were allowed to multiply if they passed a given productivity threshold. A particular property of this community is that there is no direct interaction (here, communication) amongst foragers. It is found that, still, fast compartmentalization, i.e., fast division of work can be achieved.

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