We investigate a selection-mutation model for the dynamics of technological
innovation,a special case of reaction-diffusion equations. Although mutations
are assumed to increase the variety of technologies, not their average success
("fitness"), they are an essential prerequisite for innovation. Together with a
selection of above-average technologies due to imitation behavior, they are the
"driving force" for the continuous increase in fitness. We will give analytical
solutions for the probability distribution of technologies for special cases
and in the limit of large times.
The selection dynamics is modelled by a "proportional imitation" of better
technologies. However, the assessment of a technology's fitness may be
imperfect and, therefore, vary stochastically. We will derive conditions, under
which wrong assessment of fitness can accelerate the innovation dynamics, as it
has been found in some surprising numerical investigations.Comment: For related work see http://www.helbing.or