Influence of chance, history, and adaptation on digital evolution

We evolved multiple clones of populations of digital organisms to study the effects of chance, history, and adaptation in evolution. We show that clones adapted to a specific environment can adapt to new environments quickly and efficiently, although their history remains a significant factor in their fitness. Adaptation is most significant (and the effects of history less so) if the old and new environments are dissimilar. For more similar environments, adaptation is slower while history is more prominent. For both similar and dissimilar transfer environments, populations quickly lose the ability to perform computations (the analogue of beneficial chemical reactions) that are no longer rewarded in the new environment. Populations that developed few computational "genes" in their original environment were unable to acquire them in the new environment.