Three simulators for growing artificial creatures

Artificial embryogeny aims to develop a complete organism starting from a unique cell. For years, plenty of developmental models have been introduced. The main interests are reported on morphogen positioning, differentiation mechanisms and cellular interactions. In this paper, we show how the developmental model Cell2Organ has been extended to become a multi-level simulator able to work both on morphogen positioning thanks to an hydrodynamic layer and on cellular interaction with a physical layer. Through different experiments, we show the capacities of such a model with a “muscular joint” able to move in a physical world and a small organism able to create substrate vortices thanks to the hydrodynamic engine. The inspiration of such a set of simulators is provided the gastrulation stage of vertebrate embryos. During this stage, the embryo reorganizes its environment to continue its growth.

[1]  J. Stam Real-Time Fluid Dynamics for Games , 2003 .

[2]  Karl Sims,et al.  Evolving 3d morphology and behavior by competition , 1994 .

[3]  Jos Stam A General Animation Framework for Gaseous Phenomena , 1996 .

[4]  Frisch,et al.  Lattice gas automata for the Navier-Stokes equations. a new approach to hydrodynamics and turbulence , 1989 .

[5]  W. Banzhaf Artificial Regulatory Networks and Genetic Programming , 2003 .

[6]  Vincent Fleury,et al.  Clarifying tetrapod embryogenesis, a physicist's point of view , 2009 .

[7]  Jean-Arcady Meyer,et al.  Evolution and development of neural controllers for locomotion, gradient-following, and obstacle-avoidance in artificial insects , 1998, IEEE Trans. Neural Networks.

[8]  Hervé Luga,et al.  Cell2Organ: Self-repairing artificial creatures thanks to a healthy metabolism , 2009, 2009 IEEE Congress on Evolutionary Computation.

[9]  George Konidaris,et al.  METAMorph: Experimenting with Genetic Regulatory Networks for Artificial Development , 2005, ECAL.

[10]  Thomas Bräunl,et al.  Evaluation of real-time physics simulation systems , 2007, GRAPHITE '07.

[11]  Hervé Luga,et al.  Making a Self-feeding Structure by Assembly of Digital Organs , 2009, ACAL.

[12]  Frank Dellaert,et al.  Toward an evolvable model of development for autonomous agent synthesis , 1994 .

[13]  Chrystopher L. Nehaniv,et al.  Evolution and Morphogenesis of Differentiated Multicellular Organisms - Autonomously Generated Diffusion Gradients for Positional Information , 2008, ALIFE.

[14]  Hervé Luga,et al.  From Single Cell to Simple Creature Morphology and Metabolism , 2008, ALIFE.

[15]  Mariusz Nowostawski,et al.  A Self-organising, Self-adaptable Cellular System , 2005, ECAL.

[16]  Yves Duthen,et al.  A cell pattern generation model based on an extended artificial regulatory network , 2008, Biosyst..

[17]  M. Walker Comparing the performance of incremental evolution to direct evolution , 2004 .

[18]  Phil Husbands,et al.  Asymmetric cell division and its integration with other developmental processes for artificial evolutionary systems , 2004 .

[19]  Stéphane Doncieux,et al.  Incremental Evolution of Animats' Behaviors as a Multi-objective Optimization , 2008, SAB.

[20]  Hugo de GARIS ARTIFICIAL EMBRYOLOGY AND CELLULAR DIFFERENTIATION , 1999 .

[21]  A. Boeing,et al.  Evaluation of real-time physics simulations systems , 2007 .

[22]  S. Kauffman Metabolic stability and epigenesis in randomly constructed genetic nets. , 1969, Journal of theoretical biology.

[23]  Borys Wróbel,et al.  Evolution of the Morphology and Patterning of Artificial Embryos: Scaling the Tricolour Problem to the Third Dimension , 2009, ECAL.

[24]  Peter J. Bentley,et al.  Biologically Inspired Evolutionary Development , 2003, ICES.

[25]  Y. Pomeau,et al.  Molecular dynamics of a classical lattice gas: Transport properties and time correlation functions , 1976 .