Formation of modules in a computational model of embryogeny

An investigation is conducted into the effects of a complex mapping between genotype and phenotype upon a simulated evolutionary process. A model of embryogeny is utilised to grow simple French flag like patterns. The system is shown to display a phenotypic robustness to damage and it is argued that this is a result of a modularity forming within the mapping process which causes a functional grouping of sections of the genotype

Computational Evolutionary Embryogeny

Evolutionary and developmental processes are used to evolve the configurations of 3-D structures in silico to achieve desired performances. Natural systems utilize the combination of both evolution and development processes to produce remarkable performance and diversity. However, this approach has not yet been applied extensively to the design of continuous 3-D load-supporting structures. Beginning with a single artificial cell containing information analogous to a DNA sequence, a structure is grown according to the rules encoded in the sequence. Each artificial cell in the structure contains the same sequence of growth and development rules, and each artificial cell is an element in a finite element mesh representing the structure of the mature individual. Rule sequences are evolved over many generations through selection and survival of individuals in a population. Modularity and symmetry are visible in nearly every natural and engineered structure. An understanding of the evolution and expression of symmetry and modularity is emerging from recent biological research. Initial evidence of these attributes is present in the phenotypes that are developed from the artificial evolution, although neither characteristic is imposed nor selected-for directly. The computational evolutionary development approach presented here shows promise for synthesizing novel configurations of high-performance systems. The approach may advance the system design to a new paradigm, where current design strategies have difficulty producing useful solutions

Evolutionary development of tensegrity structures

Contributions from the emerging fields of molecular genetics and evo-devo (evolutionary developmental biology) are greatly benefiting the field of evolutionary computation, initiating a promise of renewal in the traditional methodology. While direct encoding has constituted a dominant paradigm, indirect ways to encode the solutions have been reported, yet little attention has been paid to the benefits of the proposed methods to real problems. In this work, we study the biological properties that emerge by means of using indirect encodings in the context of form-finding problems. A novel indirect encoding model for artificial development has been defined and applied to an engineering structural-design problem, specifically to the discovery of tensegrity structures. This model has been compared with a direct encoding scheme. While the direct encoding performs similarly well to the proposed method, indirect-based results typically outperform the direct-based results in aspects not directly linked to the nature of the problem itself, but to the emergence of properties found in biological organisms, like organicity, generalization capacity, or modularity aspects which are highly valuable in engineering

Modularity and symmetry in computational embryogeny

Modularity and symmetry are two properties observed in almost every engineering and biological structure. The origin of these properties in nature is still unknown. Yet, as engineers we tend to generate designs which share these properties. In this paper we will report on the origin of these properties in three dimensional evolved structures (phenotypes). The phenotypes were evolved in an evolutionarydevelopmental model of biological structures. The phenotypes were grown under a high volatility stochastic environment. The phenotypes have evolved to function within the environment using the very basic requirements. Even though neither modularity nor symmetry have been directly imposed as part of the requirements, the phenotypes were able to generate these properties after only a few hundred generations. These results may suggest that modularity and symmetry are both very fundamental properties that develop during the early stages of evolution. This result may give insight to the origin of both modularity and symmetry in biological organisms

A Developmental System for Organic Form Synthesis

Abstract. Modelling the geometry of organic forms using traditional CAD or animation tools is often difficult and tedious. Different models of morphogenesis have been successfully applied to this problem; however many kinds of organic shape still pose difficulty. This paper introduces a novel system, the Simplicial Developmental System (SDS), which simulates morphogenetic and physical processes in order to generate specific organic forms. SDS models a system of cells as a dynamic simplicial complex in two or three dimensions that is governed by physical rules. Through growth, division, and movement, the cells transform the geometric and physical representations of the form. The actions of the cells are governed by conditional rules and communication between cells is supported with a continuous morphogen model. Results are presented in which simple organic forms are grown using a model inspired by limb bud development in chick embryos. These results are discussed in the context of using SDS as a creative system.

Embryomorphic Engineering: Emergent innovation through evolutionary development

Embryomorphic Engineering, a particular instance of Morpho-genetic Engineering, takes its inspiration directly from biological development to create new hardware, software or network architectures by decentralized self-assembly of elementary agents. At its core, it combines three key principles of multicellular embryogenesis: chemical gradient di usion (providing positional information to the agents), gene regulatory networks (triggering their diferentiation into types, thus patterning), and cell division (creating structural constraints, thus reshaping). This chapter illustrates the potential of Embryomorphic Engineering in di erent spaces: 2D/3D physical swarms, which can nd applications in collective robotics, synthetic biology or nan- otechnology; and nD graph topologies, which can nd applications in dis- tributed software and peer-to-peer techno-social networks. In all cases, the speci c genotype shared by all the agents makes the phenotype's complex architecture and function modular, programmable and reproducible

Diverse committees vote for dependable profits

Stock selection for hedge fund portfolios is a challenging problem for Genetic Programming (GP) because the markets (the environment in which the GP solution must survive) are dynamic, unpredictable and unforgiving. How can GP be improved so that solutions are produced that are robust to non-trivial changes in the environment? We explore an approach that uses a voting committee of GP individuals with differing phenotypic behaviour