Computer Morphogenesis in Self-Organizing Structures

Applying biological concepts to create new models in the computational field is not a revolutionary idea: science has already been the basis for the famous artificial neuron models, the genetic algorithms, etc. The cells of a biological organism are able to compose very complex structures from a unique cell, the zygote, with no need for centralized control (Watson J.D. & Crick F. H. 1953). The cells can perform such process thanks to the existence of a general plan, encoded in the DNA for the development and functioning of the system. Another interesting characteristic of natural cells is that they form systems that are tolerant to partial failures: small errors do not induce a global collapse of the system. Finally, the tissues that are composed by biological cells present parallel information processing for the coordination of tissue functioning in each and every cell that composes this tissue. All the above characteristics are very interesting from a computational viewpoint. This paper presents the development of a model that tries to emulate the biological cells and to take advantage of some of their characteristics by trying to adapt them to artificial cells. The model is based on a set of techniques known as Artificial Embryology (Stanley K. & Miikkulainen R. 2003) or Embryology Computation (Kumar S. & Bentley P.J 2003).