Bounding bloat in genetic programming
Benjamin Doerr, Timo Kötzing, J. A. Gregor Lagodzinski, Johannes Lengler · Proceedings of the Genetic and Evolutionary Computation Conference · 2017
While many optimization problems work with a fixed number of decision variables and thus a fixed-length representation of possible solutions, genetic programming (GP) works on variable-length representations. A naturally occurring problem is that of bloat (unnecessary growth of solutions) slowing down optimization. Theoretical analyses could so far not bound bloat and required explicit assumptions on the magnitude of bloat.