Scalability and Natural Computing in Artificial Morphogenesis
Dr. Allen McBride
ABSTRACT: In biological morphogenesis, thousands to quadrillions of cells self-organize to create complex structures that are functional, scalable, and robust. Artificial morphogenesis seeks to harness these properties in designed structures. The Morphgen language uses systems of partial differential equations (PDEs) to describe morphogenetic processes in the continuum limit, as spatial fields that evolve over time. I show that a generalization of smoothed particle hydrodynamics, a technique from computational fluid dynamics, can be used to discretize such PDE systems, compiling them into control laws for individual agents. This approach presents communication challenges that I address with embodied kernel functions, offloading key computation to the physical environment. In particular, cell-like agents could communicate by secreting chemicals that diffuse and are degraded in an aqueous medium. I explore in simulation the accuracy and robustness of this approach, along with strategies to mitigate gaps between simplifying assumptions and expected realities. SPEAKER BIO SUMMARY: Dr. McBride is an assistant professor at the University of North Carolina, Greensboro. He holds a BA from Swarthmore in Biology, and MA from Duke in Ecology, and a PhD in CS from University of Tennessee.