Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic programming II: automatic discovery of reusable programs
Genetic programming II: automatic discovery of reusable programs
Estimating DNA sequence entropy
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
A Representation for the Adaptive Generation of Simple Sequential Programs
Proceedings of the 1st International Conference on Genetic Algorithms
Evolving Turing-Complete Programs for a Register Machine with Self-modifying Code
Proceedings of the 6th International Conference on Genetic Algorithms
DCC '99 Proceedings of the Conference on Data Compression
Compressing XML with Multiplexed Hierarchical PPM Models
DCC '01 Proceedings of the Data Compression Conference
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
Analysing the regularity of genomes using compression and expression simplification
EuroGP'07 Proceedings of the 10th European conference on Genetic programming
Building on success in genetic programming: adaptive variation and developmental evaluation
ISICA'07 Proceedings of the 2nd international conference on Advances in computation and intelligence
Developmental evaluation in genetic programming: the preliminary results
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
Repeated patterns in tree genetic programming
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
Context-Based repeated sequences in linear genetic programming
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
IEEE Transactions on Evolutionary Computation
Representation and structural difficulty in genetic programming
IEEE Transactions on Evolutionary Computation
Applied Computational Intelligence and Soft Computing - Special issue on theory and applications of evolutionary computation
Investigating vesicular selection
Applied Soft Computing
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Shin et al [19] and McKay et al [15] previously applied tree compression and semantics-based simplification to study the distribution of building blocks in evolving Genetic Programming populations. However their method could only give static estimates of the degree of repetition of building blocks in one generation at a time, supplying no information about the flow of building blocks between generations. Here, we use a state-of-the-art tree compression algorithm, xmlppm, to estimate the extent to which frequent building blocks from one generation are still in use in a later generation. While they compared the behaviour of different GP algorithms on one specific problem -- a simple symbolic regression problem -- we extend the analysis to a more complex problem, a symbolic regression problem to find a Fourier approximation to a sawtooth wave, and to a Boolean domain, odd parity.