Redundancy creates opportunity in developmental representations

This paper investigates the influence of redundancy on the evolutionary performance of a gene regulatory network governing a cellular growth process. Redundancy is believed to play a key role in robustness and evolvability of biological systems. We use a cellular model controlled by a gene regulatory network to evolve elongated morphologies. We show that removing the redundancy in the genome during the evolution decreases the performance of the evolution strategy. A comparing run with few parameters and therefore no redundancy performs worst, which supports the hypothesis that redundancy improves evolvability. © 2011 IEEE

A fitness-independent evolvability measure for evolutionary developmental systems

Evolvability refers to the organisms ability to create heritable new phenotypes that potentially facilitate the organism's survival and reproduction. In this paper, a general evolvability measure for a computational model of evolutionary development is proposed. The measure is able to quantify individuals' evolvability, including robustness and innovation, independent of the fitness function of the evolutionary system. Empirical studies are performed to check the evolvability of individuals in in silico evolution of oscillatory behavior using the proposed evolvability measure. Our preliminary results suggest that evolvability of the developmental system can evolve without an explicit selection pressure on evolvability, confirming findings revealed in other artificial evolutionary systems

Vector Field Embryogeny

We present a novel approach toward evolving artificial embryogenies, which omits the graph representation of gene regulatory networks and directly shapes the dynamics of a system, i.e., its phase space. We show the feasibility of the approach by evolving cellular differentiation, a basic feature of both biological and artificial development. We demonstrate how a spatial hierarchy formulation can be integrated into the framework and investigate the evolution of a hierarchical system. Finally, we show how the framework allows the investigation of allometry, a biological phenomenon, and its role for evolution. We find that direct evolution of allometric change, i.e., the evolutionary adaptation of the speed of system states on transient trajectories in phase space, is advantageous for a cellular differentiation task

Global shape with morphogen gradients and motile polarized cells

Steiner T, Trommler J, Brenn M, Jin Y, Sendhoff B. Global shape with morphogen gradients and motile polarized cells. In: 2009 IEEE Congress on Evolutionary Computation. IEEE; 2009: 2225-2232.A new cellular model for evolving stable, lightweight structures is presented in this paper. The focus lies in enhancing the ability of the cellular system to create complex 3D shapes with non self-similar regions. Compared to our previous work, the model proposed in this paper is composed of polarized cells that have directionally differential force functions for cell adhesion and thus are able to follow morphogen gradients (chemotaxis). We investigate the evolution of global information in form of evolving morphogen gradients that are created prior to development, which serve to guide cellular and shape differentiation. Our analysis shows that for a set of Pareto-optimal solutions of lightweight stable structures, no unique gradient can be evolved. Nevertheless, it is revealed that neighboring individuals in the genotype space are also neighbored in the gradient space. By contrast, neighborhood in the fitness space is not maintained in the genotype space. These results suggest that a hierarchical genetic formulation might be better than a 'common predefined spatial pattern' in form of a predefined gradient. In addition, our analysis also implies that some well-known properties in direct-coding evolutionary algorithms may be lost in developmental mappings

Evolutionary Computation

This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. This book also presents new algorithms based on several analogies and metafores, where one of them is based on philosophy, specifically on the philosophy of praxis and dialectics. In this book it is also presented interesting applications on bioinformatics, specially the use of particle swarms to discover gene expression patterns in DNA microarrays. Therefore, this book features representative work on the field of evolutionary computation and applied sciences. The intended audience is graduate, undergraduate, researchers, and anyone who wishes to become familiar with the latest research work on this field

A complex systems approach to education in Switzerland

The insights gained from the study of complex systems in biological, social, and engineered systems enables us not only to observe and understand, but also to actively design systems which will be capable of successfully coping with complex and dynamically changing situations. The methods and mindset required for this approach have been applied to educational systems with their diverse levels of scale and complexity. Based on the general case made by Yaneer Bar-Yam, this paper applies the complex systems approach to the educational system in Switzerland. It confirms that the complex systems approach is valid. Indeed, many recommendations made for the general case have already been implemented in the Swiss education system. To address existing problems and difficulties, further steps are recommended. This paper contributes to the further establishment complex systems approach by shedding light on an area which concerns us all, which is a frequent topic of discussion and dispute among politicians and the public, where billions of dollars have been spent without achieving the desired results, and where it is difficult to directly derive consequences from actions taken. The analysis of the education system's different levels, their complexity and scale will clarify how such a dynamic system should be approached, and how it can be guided towards the desired performance