Co-Evolving Intertwined Spirals.
Hugues Juillé, Jordan B. Pollack · 1996
We recently solved the two spirals problem, a difficult neural network benchmark classification problem, using the genetic programming primitives set up by [Koza, 1992]. Instead of using absolute fitness, we use a relative fitness based on a competition for coverage of the data set. This is a form of co-evolutionary search because the fitness function changes with the population. Because niches are opened by proportionate reproduction, rather than crowded out, and because of the crossover operator, we find solutions which have a nice modular structure. Our experiments used our Massively Parallel Genetic Programming (MPGP) system running on a SIMD machine of 4096 processors, the Maspar MP-2.