We study both genotypic and phenotypic convergence in GP floating point continuous
domain symbolic regression over thousands of generations. Subtree fitness variation across …

We evolve floating point Sextic polynomial populations of genetic programming binary trees
for up to a million generations. We observe continued innovation but this is limited by tree …

It is 30 years since John R. Koza published “Jaws”, the first book on genetic programming
[Genetic Programming: On the Programming of Computers by Means of Natural Selection …

With side effect free terminals and functions it is possible to evaluate the fitness of genetic
programming trees from their parents without creating them. This allows selection before …

Figure 2 shows a large nested function composed of floating point arithmetic operations (+,-
,× and÷). Each function acts as a two input information funnel and loses information. The red …

We inject a random value into the evaluation of highly evolved deep integer GP trees 9 743
720 times and find 99.7% of test outputs are unchanged. Suggesting crossover and …

For the goal of automatically evolving Embodied Intelligence (EI), we investigate an open
software architecture inspired by the high surface area to volume ratio of animal lungs …

Information theory explains the robustness of deep GP trees, with on average up to 83.3% of
crossover run time disruptions failing to propagate to the root node, and so having no impact …

Information-theoretic analysis of large, evolved programs produced by running genetic
programming for up to a million generations has shown even functions as smooth and well …

We sample the genetic programming tree search space and show it is smooth, since many
mutations on many test cases have little or no fitness impact. We generate uniformly at …