There is a good Ted Talk movie about the Physarum Polycephalum that Victor mentioned. The mold's goal is its favorite food, oats. The mold found the shortest path through a maze. Researchers blew cold air, which the mold dislikes, on it at a given interval. The mold slowed its growth at that spot at the given interval even after the blowing was stopped, exhibiting memory and learning. It replicated Tokyo's transport system after oats were placed at town locations. The mold has no brain and has no central nervous system, but does have a fan club, SliMoCo. TED Talk http://www.ted.com/talks/heather_barnett_what_humans_can_learn_from_semi_int... SliMoCo - The Slime Mould Collective http://slimoco.ning.com/ Michael Desai, a Harvard biophysicist and head of the Desai Lab, is part of a team that took a single yeast cell, developed 432 independent lines, grew them separately for 240 generations, from them selected 64 lines with differing fitnesses, and ended up with 640 lines that grew over 500 generations. Lines less fit at the beginning evolved more rapidly, but all the lines converged to the same fitness level. It was as if the genes were performing a search, each line in parallel, and had taken different paths to the same solution. The paper's title says it all, and seems to me to be a plausible explanation for the success of the ant colony algorithms Henry mentioned. Global Epistasis Makes Adaptation Predictable Despite Sequence-Level Stochasticity. "http://www.sciencemag.org/content/344/6191/1519.full.pdf?ijkey=nZiFADaPb3Kck... The Desai Lab http://www.oeb.harvard.edu/faculty/desai/index.html On Sat, Sep 13, 2014 at 12:09 AM, Henry Baker <hbaker1@pipeline.com> wrote:

Yes, there are a whole bunch of "ant colony"-type algorithms that have been studied, trying to figure how how large numbers of parallel computers and/or robots can solve certain tasks.

At 12:29 PM 9/12/2014, Victor Miller wrote:

...

Does this qualify: http://arxiv.org/abs/1106.0423 ?

Victor

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