Genetic Programming and Evolvable Machines

Papers
(The TQCC of Genetic Programming and Evolvable Machines is 3. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-05-01 to 2024-05-01.)
ArticleCitations
An enhanced Huffman-PSO based image optimization algorithm for image steganography30
Choosing function sets with better generalisation performance for symbolic regression models18
Graph representations in genetic programming13
TPOT-NN: augmenting tree-based automated machine learning with neural network estimators13
Genetic programming convergence11
Evolutionary approximation and neural architecture search9
Evolving hierarchical memory-prediction machines in multi-task reinforcement learning8
Applying genetic programming to PSB2: the next generation program synthesis benchmark suite8
Semantically-oriented mutation operator in cartesian genetic programming for evolutionary circuit design7
Interpretability in symbolic regression: a benchmark of explanatory methods using the Feynman data set6
Blood glucose prediction using multi-objective grammatical evolution: analysis of the “agnostic” and “what-if” scenarios6
Tag-based regulation of modules in genetic programming improves context-dependent problem solving5
Fuzzy cognitive maps for decision-making in dynamic environments5
Complexity and aesthetics in generative and evolutionary art5
Symbolic-regression boosting4
Constant optimization and feature standardization in multiobjective genetic programming4
Severe damage recovery in evolving soft robots through differentiable programming4
Virginia Dignum: Responsible Artificial Intelligence: How to Develop and Use AI in a Responsible Way3
Evolving continuous optimisers from scratch3
On the performance of the Bayesian optimization algorithm with combined scenarios of search algorithms and scoring metrics3
Evolutionary algorithms for designing reversible cellular automata3
A grammar-based GP approach applied to the design of deep neural networks3
Software review: Pony GE23
Feature extraction by grammatical evolution for one-class time series classification3
Experiments in evolutionary image enhancement with ELAINE3
GP-DMD: a genetic programming variant with dynamic management of diversity3
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