At a first glance the problem of novelty creation in computers actually does not appear to be a problem at all. Computer models are nothing but algorithms and as such unable to transcend the boundaries of their own world which has been created by the modeller. However, the general feeling is that we can simulate with arbitrary degree of precision the objects we find in nature; then, assuming that the latter is capable of creating novelty, we can ask: ``Why should it not be possible to create novelty in computers if nature can do it?'' One possible answer might be that novelty creation critically depends on the complexity of nature; this complexity, one might argue, cannot be mirrored in computer models because the time needed to implement and run such a complex model would exceed all limits of available human and financial resources--see Gross & Jefferies (2001).
Although this answer might be valid for some types of problems, it potentially misses an important point. Nature might be complex on some levels, but is often assumed to be simple at the level of elementary particle physics and chemistry which are the most fundamental levels. This assumption of, and quest for, simplicity of the most fundamental laws of nature was introduced by Galilei. Free after Galilei, one might now look for artificial (= computer simulated) worlds which are both simple (in the sense that they function according to only a few comprehensive laws), but at the same time are able to create complexity of arbitrary degree. Prima facie then, there is no reason why this should not be possible using today's sophisticated technology and methodological tools.
The question of the creation of novelty in computer models is a central one for Artificial Life. If ever credible life-forms or evolutionary processes in silico are to be realised, then at least they have to have the capability to generate novelty. The question is also interesting on a more philosophical level: if we consider life as an essentially algorithmic process, then it should be possible to mimic its most important features in a computer-based model; we have only to figure out the ``right'' algorithm(s). On the other hand, it might also be that life is fundamentally non-algorithmic--see for example Rosen (1991).
The concept of novelty we have in mind in this paper is clearly closely related to complexity in the informal sense formulated by John von Neumann (von Neumann, 1949, p. 78); and the creation of novelty then corresponds to the (evolutionary?) growth of complexity (McMullin, 2000). Nonetheless we deliberately choose the term ``novelty'' in this case, so that its natural vagueness and subjectivity may serve to emphasise the ill-defined nature of the problems under discussion.
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