Behavior-Finding: Morphogenetic Designs Shaped by Function

Abstract

Evolution has shaped an incredible diversity of multicellular living organisms, whose complex forms are self-made through a robust developmental process. This fundamental combination of biological evolution and development has served as an inspiration for novel engineering design methodologies, with the goal to overcome the scalability problems suffered by classical top-down approaches. Top-down methodologies are based on the manual decomposition of the design into modular, independent subunits. In contrast, recent computational morphogenetic techniques have shown that they were able to automatically generate truly complex innovative designs. Algorithms based on evolutionary computation and artificial development have been proposed to automatically design both the structures, within certain constraints, and the controllers that optimize their function. However, the driving force of biological evolution does not resemble an enumeration of design requirements, but much rather relies on the interaction of organisms within the environment. Similarly, controllers do not evolve nor develop separately, but are woven into the organism's morphology. In this chapter, we discuss evolutionary morphogenetic algorithms inspired by these important aspects of biological evolution. The proposed methodologies could contribute to the automation of processes that design "organic" structures, whose morphologies and controllers are intended to solve a functional problem. The performance of the algorithms is tested on a class of optimization problems that we call behavior-finding. These challenges are not explicitly based on morphology or controller constraints, but only on the solving abilities and efficacy of the design. Our results show that morphogenetic algorithms are well suited to behavior-finding.

A review of morphogenetic engineering

“…Although a plant's architecture contains an intrinsic, genetically determined part, its morphogenesis also exhibits very high plasticity with respect to environmental conditions. This could be mediated by a self-regulatory Lobo and Vico [104,55] (Fig. 2:17) have also worked on evolutionary morphogenetic algorithms of the generative kind to automate the design of "organic" morphologies and controllers with the goal of solving certain functional problems.…”

Melomics: A Case‐Study of AI in Spain

“…Our group has successfully developed and applied this paradigm of artificial development to two different domains in Column FALL 2013 101 computational creativity: new techniques for automatic character animation (Lobo, Fernández, and Vico 2012), and new systems for algorithmic composition.…”

“…Remarkable examples of real‐life applications of artificial development have appeared in recent years, such as the set of antennas designed to fit the technical requirements for the satellites of a NASA space mission (Hornby, Lohn., and Linden 2011); the design of microstructured optical fibers (Manos, Large, and Poladian 2007); and the automatic generation of board games (Browne 2008). Our group has successfully developed and applied this paradigm of artificial development to two different domains in computational creativity: new techniques for automatic character animation (Lobo, Fernández, and Vico 2012), and new systems for algorithmic composition.…”

“…creativity: new techniques for automatic character animation(Lobo, Fernández, and Vico 2012), and new systems for algorithmic composition.…”