  Motivated by a desire to improve on the current state of the art in genetic
programming, and aided by recent progress in understanding the computational
aspects of evolutionary systems, we describe a process that creates a set of
generic computational building blocks for the purpose of seeding initial
populations of programs in any genetic programming system. This provides an
advantage over the standard approach of initializing the population purely
randomly in that it avoids the need to constantly rediscover such building
blocks. It is also better than seeding the initial population with hand-coded
building blocks, since it lessens the amount of human intervention required by
the system.
