English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Why are living systems complex? Why does the biosphere contain living beingswith complexity features beyond those of the simplest replicators? What kind ofevolutionary pressures result in more complex life forms? These are keyquestions that pervade the problem of how complexity arises in evolution. Oneparticular way of tackling this is grounded in an algorithmic description oflife: living organisms can be seen as systems that extract and processinformation from their surroundings in order to reduce uncertainty. Here wetake this computational approach using a simple bit string model of coevolvingagents and their parasites. While agents try to predict their worlds, parasitesdo the same with their hosts. The result of this process is that, in order toescape their parasites, the host agents expand their computational complexitydespite the cost of maintaining it. This, in turn, is followed by increasinglycomplex parasitic counterparts. Such arms races display several qualitativephases, from monotonous to punctuated evolution or even ecological collapse.Our minimal model illustrates the relevance of parasites in providing an activemechanism for expanding living complexity beyond simple replicators, suggestingthat parasitic agents are likely to be a major evolutionary driver forbiological complexity.

How Turing parasites expand the computational landscape of digital life