A Theoretical and Applicative Framework for Evolutive Computers

With the generalisation of massively parallel systems, computer engineering lifts a new scientific challenge: that of formulating an evolution theory, able to rule the self-organisation of artificial collectivities and individuals, inducing a rise in their performance, ability, reliability, and robustness; in other words, a theory which would ground their viability and intelligence. Towards this goal, genetic algorithms provide a framework both conceptually new and powerful on the computational side. However, this computer engineering prospect for evolution stays insufficient in many respects. The work we present aims at expressing a theory of evolution which counters the weaknesses of genetic algorithms. Essentially, we seek to heighten their operationnality by refining the darwinian model upon which they are based, to enable a fast replay of the history of life over silicon components. In practice, we suggest a reinstatement of Lamarckian laws, leading to a view reconciling construct..