TY  - JOUR
N1  - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions.
TI  - Genetic programming convergence
AV  - public
SP  - 71
VL  - 23
Y1  - 2021/03//
EP  - 104
JF  - Genetic Programming and Evolvable Machines
A1  - Langdon, WB
KW  - Evolutionary computation
KW  -  stochastic search
KW  -  diversity
KW  -  bottom up
incremental evaluation
KW  -  PIE
KW  -  propagation
KW  -  infection
KW  -  and execution
KW  -  SIMD parallel processing
KW  -  AVX vector instructions
N2  - We study both genotypic and phenotypic convergence in GP floating point continuous domain symbolic regression over thousands of generations. Subtree fitness variation across the population is measured and shown in many cases to fall. In an expanding region about the root node, both genetic opcodes and function evaluation values are identical or nearly identical. Bottom up (leaf to root) analysis shows both syntactic and semantic (including entropy) similarity expand from the outermost node. Despite large regions of zero variation, fitness continues to evolve and near zero crossover disruption suggests improved GP systems within existing memory use.
ID  - discovery10146198
UR  - https://doi.org/10.1007/s10710-021-09405-9
PB  - Springer Verlag
ER  -