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Automated shape composition based on cell biology and distributed genetic programming
Conference proceeding   Open access

Automated shape composition based on cell biology and distributed genetic programming

Linge Bai, Manolya Eyiyurekli and David Breen
Proceedings of the 10th annual conference on genetic and evolutionary computation, pp 1179-1186
12 Jul 2008
DOI: https://doi.org/10.1145/1389095.1389329
url
https://doi.org/10.1145/1389095.1389329View
Published, Version of Record (VoR)Open Access (License Unspecified),  Open

Abstract

chemotaxis distributed genetic programming morphogenesis self-organization shape composition
Motivated by the ability of living cells to form specific shapes and structures, we present a computational approach using distributed genetic programming to discover cell-cell interaction rules for automated shape composition. The key concept is to evolve local rules that direct virtual cells to produce a self-organizing behavior that leads to the formation of a macroscopic, user-de.ned shape. The interactions of the virtual cells, called Morphogenic Primitives (MPs), are based on chemotaxis-driven aggregation behaviors exhibited by actual living cells. Cells emit a chemical into their environment. Each cell responds to the stimulus by moving in the direction of the gradient of the cumulative chemical field detected at its surface. MPs, though, do not attempt to completely mimic the behavior of real cells. The chemical fields are explicitly defined as mathematical functions and are not necessarily physically accurate. The functions are derived via a distributed genetic programming process. A fitness measure, based on the shape that emerges from the chemical-field-driven aggregation, determines which functions will be passed along to later generations. This paper describes the cell interactions of MPs and a distributed genetic programming method to discover the chemical fields needed to produce macroscopic shapes from simple aggregating primitives.

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