Abstract: |
Evolutionary computation has been often used by computer scientists to evolve the morphologies and control systems of artificial life. Artificial 'brains', behaviour strategies, methods of communication, distributed problem solving and many other topics are commonly explored by using genetic algorithms and other evolutionary search techniques. We think that this approach may provide the general guidelines to efficiently manage and "design" computation on large and homogeneous lattices of simple, asynchronously interacting processing elements. Because of their structural simplicity, this kind of substrates will be suitable architectural models for computational machines based on molecular scale devices. In this paper we present an environment named Bio-molecular Engine (BME), in which different substrates can be simulated and used as "artificial worlds" where computational entities can rise, grow and evolve. In particular we discuss how to use a grid to evolutionary find a good solution to a well defined design issue: how much parallelism is good for a given problem computed in our environment. |
