abstract = "This paper demonstrates a technique that reduces the
time and space requirements of genetic programming. The
population of parse trees is stored as a directed
acyclic graph (DAG), rather than as a forest of trees.
This saves space by not duplicating structurally
identical subtrees. Also, the value computed by each
subtree for each fitness case is cached, which saves
computation both by not recomputing subtrees that
appear more than once in a generation and by not
recomputing subtrees that are copied from one
generation to the next. I have implemented this
technique for a number of problems and have seen a 15-
to 28-fold reduction in the number of nodes extant per
generation and an 11- to 30-fold reduction in the
number of nodes evaluated per run (for populations of
notes = "Converts whole GP population to a directed Acyclic
Graph, which is functionally equivelent. With
primatives that have NO SIDE EFFECTS is able to cache
earlier sub tree evaluations so they donot have to be
re-evaluated, even if occur in a different individual.
Claims speed ups of 11-30 fold.