My weekly Pubcrawler search turned up an interesting computer and information science paper this week, in the journal Artificial Life – Evolution and development of a multicellular organism: scalability, resilience, and neutral complexification.
I’m having trouble accessing the full text, and I’d very much like to read it, because these are characteristics of biocomplexity that we could define a bit more thoroughly in explaining the molecular basis for evolution, I think. So, if anyone has the PDF for this paper (abstract below the fold), would you be so kind as to send it to me? Very intersting paper, that I’ll read thoroughly tonight, and comment more on tomorrow. At first glance, however, it seems to be a must-read for any and all “confused” laypersons out there who are daunted by the imense complexity of the metazoan cell, and evolution of said complexity.
I’m sure it’s the sort of thing that Hannah and other Cornell IDers will resolutely do their best to ignore…
To increase the evolvability of larger search spaces, several indirect encoding strategies have been proposed. Among these, multicellular developmental systems are believed to offer great potential for the evolution of general, scalable, and self-repairing organisms. We reinforce this view, presenting the results achieved by such a model and comparing it against direct encoding. Extra effort has been made to make this comparison both general and meaningful. Embryonal stages, a generic method showing increased evolvability and applicable to any developmental model, are introduced. Development with embryonal stages implements what we refer to as direct neutral complexification: direct genotype complexification by neutral duplication of expressed genes. The results show that, even for high-complexity evolutionary targets, the developmental model proves more scalable. The model also shows emergent self-repair, which is used to produce highly resilient organisms.