  Information theoretic analysis of large evolved programs produced by running
genetic programming for up to a million generations has shown even functions as
smooth and well behaved as floating point addition and multiplication loose
entropy and consequently are robust and fail to propagate disruption to their
outputs. This means, while dependent upon fitness tests, many genetic changes
deep within trees are silent. For evolution to proceed at reasonable rate it
must be possible to measure the impact of most code changes, yet in large trees
most crossover sites are distant from the root node. We suggest to evolve very
large very complex programs, it will be necessary to adopt an open architecture
where most mutation sites are within 10 to 100 levels of the organism's
environment.
