Classical Sorting Algorithms Reveal Unexpected Competencies in a Minimal Model of Basal Intelligence
A new study uses classical sorting algorithms as a model of morphogenesis, challenging conventional wisdom about these algorithms. By breaking assumptions of top-down control and perfectly reliable hardware, researchers discovered that arrays of autonomous elements sort themselves more reliably and robustly than traditional implementations, even in the presence of errors. Surprisingly, these algorithms exhibit the ability to temporarily reduce progress to navigate around defects and unexpected clustering behavior among elements in chimeric arrays following different algorithms. This discovery provides a novel perspective on diverse intelligence, demonstrating how basal forms of intelligence can emerge in simple systems without explicit encoding in their underlying mechanics.
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