Robust Engineering Using Biologically-Inspired Models of Cell Differentiation and Morphogenesis

The Problem: In this research, we propose to use morphogenesis and developmental biology as a source of al-gorithms and general principles for organizing complex behavior from locally interacting individuals. We aim to design artificial systems that replicate biological robustness, and to use insights from these systems to understand the capabilities of biological systems. The goal is to be able to formalize these general principles as programming languages — with explicit primitives, means of combination, and means of abstraction — thus providing a frame-work for the design and analysis of self-assembling systems. Motivation: Within the next decade, emerging technologies will make possible novel applications that integrate computation into the environment: smart materials, self-reconfiguring robots, self-assembling nanostructures. We are faced with the challenge of achieving coherent and robust behavior from the interactions of multitudes of el-ements and their interactions with the environment. These new environments fundamentally stress the limits of our current engineering and programming techniques, which depend on precision parts and strongly regulated environments to achieve fault-tolerance. By contrast, the precision and reliability of embryogenesis, in the face of unreliable cells, variations in cell numbers, and changes in the environment, is enough to make any engineer green with envy. We believe that important organizational lessons can be learned from natural biological systems. Previous Work: Nagpal has demonstrated the power of the programming-language approach by developing