  Although information content is invariant up to an additive constant, the
range of possible additive constants applicable to programming languages is so
large that in practice it plays a major role in the actual evaluation of K(s),
the Kolmogorov-Chaitin complexity of a string s. Some attempts have been made
to arrive at a framework stable enough for a concrete definition of K,
independent of any constant under a programming language, by appealing to the
"naturalness" of the language in question. The aim of this paper is to present
an approach to overcome the problem by looking at a set of models of
computation converging in output probability distribution such that that
"naturalness" can be inferred, thereby providing a framework for a stable
definition of K under the set of convergent models of computation.
