Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
The algorithmic beauty of plants
The algorithmic beauty of plants
Evolving programmers: the co-evolution of intelligent recombination operators
Advances in genetic programming
Extending genetic programming with recombinative guidance
Advances in genetic programming
Two self-adaptive crossover operators for genetic programming
Advances in genetic programming
Numerical Optimization of Computer Models
Numerical Optimization of Computer Models
Genetic Programming and Evolvable Machines
An overview of evolutionary algorithms for parameter optimization
Evolutionary Computation
Analysing the regularity of genomes using compression and expression simplification
EuroGP'07 Proceedings of the 10th European conference on Genetic programming
Developmental evaluation in genetic programming: the preliminary results
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
Representation and structural difficulty in genetic programming
IEEE Transactions on Evolutionary Computation
Learning General Solutions through Multiple Evaluations during Development
ICES '08 Proceedings of the 8th international conference on Evolvable Systems: From Biology to Hardware
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Developmental plasticity in linear genetic programming
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Semantically-based crossover in genetic programming: application to real-valued symbolic regression
Genetic Programming and Evolvable Machines
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We investigate a developmental tree-adjoining grammar guided genetic programming system (DTAG3P+), in which genetic operator application rates are adapted during evolution. We previously showed developmental evaluation could promote structured solutions and improve performance in symbolic regression problems. However testing on parity problems revealed an unanticipated problem, that good building blocks for early developmental stages might be lost in later stages of evolution. The adaptive variation rate in DTAG3P+ preserves good building blocks found in early search for later stages. It gives both good performance on small k-parity problems, and good scaling to large problems.