1. Evolved Developmental Strategies of Artificial Multicellular Organisms
- Author
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Yves Duthen, Jean Disset, Sylvain Cussat-Blanc, Institut National Polytechnique de Toulouse - INPT (FRANCE), Centre National de la Recherche Scientifique - CNRS (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), Real Expression Artificial Life (IRIT-REVA), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, and Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
- Subjects
02 engineering and technology ,Biology ,01 natural sciences ,Outcome (game theory) ,[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] ,Traitement des images ,Local optimum ,[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing ,Cell cluster ,0202 electrical engineering, electronic engineering, information engineering ,Traitement du signal et de l'image ,0101 mathematics ,Physics engine ,H- INFORMATIQUE ,Synthèse d'image et réalité virtuelle ,Organism ,business.industry ,010102 general mathematics ,Novelty ,[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] ,Vision par ordinateur et reconnaissance de formes ,Intelligence artificielle ,[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR] ,Multicellular organism ,[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] ,Metric (mathematics) ,3D physics model ,020201 artificial intelligence & image processing ,Artificial intelligence ,business - Abstract
International audience; We present the use of a new computationaly efficient 3D physics model for the simulation of cells in a virtual aquatic world. In this model, cells can freely assemble and disconnect along the simulation without any separation between the development and evaluation stages, as is the case in most evo-devo models which only consider one cell cluster. While allowing for the discovery of interesting behaviors through the addition of new degrees of freedom, this 3D center-based physics engine and its associated virtual world also come with their drawbacks when applied to evolutionnary experiments: larger search space and numerous local optima. In this paper, we have designed an experiment in which cells must learn to survive by keeping their genome alive as long as possible in a demanding world. No morphology or strategy is explicitly enforced; the only objective the cells have to optimize is the survival time of the organism they build. We show that a novelty metric, adapted to our evo-devo matter, dramatically improves the outcome of the evolutionary runs. This paper also details some of the developmental strategies the evolved multicellular organisms have found in order to survive.
- Published
- 2016