No abstract

We present the use of a new computationaly efficient 3D physics model for the simulation of cells in a virtual sea world. In this model, cells can freely assemble and disconnect along the simulation without any separation between the developmental 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. We show that a novelty metric, adapted to our evo-devo matter, 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.

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We present an open source physics engine specialised for multi-cellular artificial organisms simulations. It is computationally efficient in comparison to gas-based and finite element models and more realistic than standard mass-springdamper systems.

This paper presents a new model for the development of artificial creatures from a single cell. The model aims at providing a more biologically plausible abstraction of the morphogenesis and the specialization process, which the organogenesis follows. It is built upon three main elements: a cellular physics simulation, a simplified cell cycle using an evolved artificial gene regulatory network and a cell specialization mechanism quantifying the ability to perform different functions. As a proof-of-concept, we present a small experiment where the morphology of a multicellular organism is guided by cell weaknesses and efficiency at performing different functions under environmental stress.