Recombination, selection, and the genetic construction of computer programs
Recombination, selection, and the genetic construction of computer programs
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Complexity Compression and Evolution
Proceedings of the 6th International Conference on Genetic Algorithms
Modification point depth and genome growth in genetic programming
Evolutionary Computation
A learning system based on genetic adaptive algorithms
A learning system based on genetic adaptive algorithms
Operator equalisation for bloat free genetic programming and a survey of bloat control methods
Genetic Programming and Evolvable Machines
| Hi-index | 0.00 |
The C-value Paradox is the name given in biology to the wide variance in and often very large amount of DNA in eukaryotic genomes and the poor correlation between DNA length and perceived organism complexity. Several hypotheses exist which purport to explain the Paradox. Surprisingly there is a related phenomenon in evolutionary computation, known as code bloat, for which a different set of hypotheses has arisen. This paper describes a new hypothesis for the C-value Paradox derived from models of code bloat. The new explanation is that there is a selective bias in preference of genetic events which increase DNA material over those which decrease it. The paper suggests one possible concrete mechanism by which this may occur: deleting strands of DNA is more likely to damage genomic material than migrating or copying strands. The paper also discusses other hypotheses in biology and in evolutionary computation, and provides a simulation example as a proof of concept.