Evolution unbound: releasing the arrow of complexity

Biology and Philosophy 26 (3):317-338 (2011)
The common opinion has been that evolution results in the continuing development of more complex forms of life, generally understood as more complex organisms. The arguments supporting that opinion have recently come under scrutiny and been found wanting. Nevertheless, the appearance of increasing complexity remains. So, is there some sense in which evolution does grow complexity? Artificial life simulations have consistently failed to reproduce even the appearance of increasing complexity, which poses a challenge. Simulations, as much as scientific theories, are obligated at least to save the appearances! We suggest a relation between these two problems, understanding biological complexity growth and the failure to model even its appearances. We present a different understanding of that complexity which evolution grows, one that genuinely runs counter to entropy and has thus far eluded proper analysis in information-theoretic terms. This complexity is reflected best in the increase in niches within the biosystem as a whole. Past and current artificial life simulations lack the resources with which to grow niches and so to reproduce evolution’s complexity. We propose a more suitable simulation design integrating environments and organisms, allowing old niches to change and new ones to emerge
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DOI 10.1007/s10539-011-9254-6
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Claude Shannon (1948). A Mathematical Theory of Communication. Bell System Technical Journal 27:379–423.
Richard Dawkins (1999). Climbing Mount Improbable. Environmental Values 8 (1):114-116.
Christoph Adami (2002). What is Complexity? Bioessays 24 (12):1085-1094.

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Peter Jedlicka (2007). Physical Complexity and Cognitive Evolution. In Carlos Gershenson, Diederik Aerts & Bruce Edmonds (eds.), Worldviews, Science, and Us: Philosophy and Complexity. World Scientific. pp. 221--231.
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