Embryogeny and Grid Computing

AbstractIn Arti cial Life, the production of new arti cial creatures always needs more andmore computation power. Whereas arti cial morphogenesis methods construct com-plete creatures using blocks, arti cial embryogeny develops smaller creatures start-ing from a unique cell. To obtain a complete creature, organized in tissues andorgans, we propose a developmental model in which cells are coded as threads. Thismassive parallel architecture allows the simulation of an organism development onmulti-core or multi-processor machines. In most cases, evolutionary algorithms andespecially genetic algorithms are used to create our creatures. Their algorithmstake a lot of computation time to nd an environment-adapted creature. In orderto reduce the computation time, genetic algorithms have already been parallelized,but, in most cases, using a supercomputer. This solution is very expensive and noteasily scalable. In this report, we rst present our model of arti cial embryogeny,Cell2Organ. Then, we propose an implementation of genetic algorithms for arti cialembryogeny using a computational grid and ProActive middleware.