Morphogenesis

"We apply novel analyses to the behavior of classical sorting algorithms —short pieces of code studied for many decades. 

"To study these sorting algorithms as a model of biological morphogenesis and its competencies, we break two formerly ubiquitous assumptions: top-down control (instead, each element within an array of numbers can exert minimal agency and implement sorting policies from the bottom up), and fully reliable hardware (instead, allowing elements to be 'damaged' and fail to execute the algorithm). 

"We quantitatively characterize sorting activity as traversal of a problem space, showing that arrays of autonomous elements sort themselves more reliably and robustly than traditional implementations in the presence of errors. 

'Moreover, we find the ability to temporarily reduce progress in order to navigate around a defect, and unexpected clustering behavior among elements in chimeric arrays consisting of two different algorithms."

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