Changes to Genetic Programing Bibliography since 2024/10/14

New

1. DBLP:conf/eurocast/AffenzellerBDDH19 White Box vs. Black Box Modeling: On the Performance of Deep Learning, Random Forests, and Symbolic Regression in Solving Regression Problems MichaelAffenzeller.html BogdanBurlacu.html ViktoriaDorfer.html SebastianDorl.html GerhardHalmerbauer.html TilmanKoenigswieser.html MichaelKommenda.html JuliaVetter.html StephanMWinkler.html
2. bensoussan2024acceleratingquantumeigensolveralgorithms Accelerating Quantum Eigensolver Algorithms With Machine Learning AvnerBensoussan.html ElenaChachkarova.html KarineEven-Mendoza.html SophieFortz.html ConnorLenihan.html
3. Boldi:2024:ALife Untangling the Effects of Down-Sampling and Selection in Genetic Programming RyanBoldi.html AshleyBao.html MartinBriesch.html ThomasHelmuth.html DominikSobania.html LeeSpector.html AlexanderLalejini.html
4. Boldi:ECJ Informed Down-Sampled Lexicase Selection: Identifying Productive Training Cases for Efficient Problem Solving RyanBoldi.html MartinBriesch.html DominikSobania.html AlexanderLalejini.html ThomasHelmuth.html FranzRothlauf.html CharlesOfria.html LeeSpector.html
5. Brownlee:2024:ASE Large Language Model Based Mutations in Genetic Improvement AlexanderEIBrownlee.html JamesCallan.html KarineEven-Mendoza.html AlinaGeiger.html CarolHanna.html JustynaPetke.html FedericaSarro.html DominikSobania.html
6. Chang:2020:AIdrug Swarm and Evolutionary Intelligence MarkChang.html
7. defranca2023interpretablesymbolicregressiondata Interpretable Symbolic Regression for Data Science: Analysis of the 2022 Competition FabricioOlivettideFranca.html MarcoVirgolin.html MichaelKommenda.html MaimunaMajumder.html MilesCranmer.html GuilhermeJorgeNunesMonteiroEspada.html LeonIngelse.html AlcidesFonseca.html MikelLandajuela.html BrendenKylePetersen.html RubenGlatt.html TNathanMundhenk.html ChakShingLee.html JacobDeanHochhalter.html DavidLRandall.html Pierre-AlexandreKamienny.html HengzheZhang.html GrantDick.html AlessandroSimon.html BogdanBurlacu.html JaanKasak.html MeeraMachado.html CasperWilstrup.html WilliamLaCava.html
8. ding:2022:LEOL Lexicase Selection at Scale LiDing.html RyanBoldi.html ThomasHelmuth.html LeeSpector.html
9. Dong:ieeeTEC Evolving Equation Learner For Symbolic Regression JunlanDong.html JinghuiZhong.html WeiliLiu.html JunZhang.html
10. Espinal:2024:CyS Grammatical Evolution with Codons Selection Order as Intensification Process AndresEspinalJimenez.html MarcoAurelioSoteloFigueroa.html JorgeAlbertoSoria-Alcaraz.html
11. GilGala:2024:AI Evolving routing policies for electric vehicles by means of genetic programming FranciscoJavierGilGala.html MarkoDurasevic.html DomagojJakobovic.html
12. Gupt:thesis Gupt:thesis KrishnKumarGupt.html
13. Gupt:2024:fcomp A novel ML-driven test case selection approach for enhancing the performance of grammatical evolution KrishnKumarGupt.html MeghanaKshirsagar.html DouglasMotaDias.html JoeSullivan.html ConorRyan.html
14. Haut:ieeeTEC Active Learning in Genetic Programming: Guiding Efficient Data Collection for Symbolic Regression NathanielHaut.html WolfgangBanzhaf.html WilliamFPunch.html
15. DBLP:conf/eurocast/KammererKK22 Symbolic Regression with Fast Function Extraction and Nonlinear Least Squares Optimization LukasKammerer.html GabrielKronberger.html MichaelKommenda.html
16. khattab2023dspycompilingdeclarativelanguage DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines OmarKhattab.html ArnavSinghvi.html ParidhiMaheshwari.html ZhiyuanZhang.html KeshavSanthanam.html SriVardhamananA.html SaifulHaq.html AshutoshSharma.html ThomasTJoshi.html HannaMoazam.html HeatherMiller.html MateiAZaharia.html ChristopherPotts.html
17. Khattab:2023:neurips DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines OmarKhattab.html ArnavSinghvi.html ParidhiMaheshwari.html ZhiyuanZhang.html KeshavSanthanam.html SriVardhamananA.html SaifulHaq.html AshutoshSharma.html ThomasTJoshi.html HannaMoazam.html HeatherMiller.html MateiAZaharia.html ChristopherPotts.html
18. Kocherovsky:2024:ALife Crossover Destructiveness in Cartesian versus Linear Genetic Programming MarkKocherovsky.html WolfgangBanzhaf.html
19. Kosorukov:2024:ASENIER Mining for Mutation Operators for Reduction of Information Flow Control Violations IlyaKosorukov.html DanielBlackwell.html DavidClark.html MyraBCohen.html JustynaPetke.html
20. Lalejini:2022:eLife Artificial selection methods from evolutionary computing show promise for directed evolution of microbes AlexanderLalejini.html EmilyDolson.html AnyaEVostinar.html LuisZaman.html
21. langdon:2024:ASE Deep Imperative Mutations have Less Impact WilliamBLangdon.html DavidClark.html
22. Liou:TELO Evolving to find optimizations humans miss: using evolutionary computation to improve GPU code for bioinformatics applications Jhe-YuLiou.html MuaazGulAwan.html KirtusLeyba.html PetrSulc.html StevenAHofmeyr.html Carole-JeanWu.html StephanieForrest.html
23. Lourenco:thesis Enhancing Grammar-Based Approaches for the Automatic Design of Algorithms NunoLourenco.html
24. Mahdinejad:thesis Optimizing Convolutional Neural Network Segmentation Tasks Using Evolutionary Algorithms MahsaMahdinejad.html
25. Murphy:2024:GPEM An investigation into structured grammatical evolution initialisation AidanMurphy.html MahsaMahdinejad.html AnthonyVentresque.html NunoLourenco.html
26. Nemeth:2024:ALife Phenotypic Species Definitions for Genetic Improvement of Source Code ZsoltNemeth.html PenelopeFaulknerRainford.html BarryPorter.html
27. DBLP:conf/eurocast/ParraJGVGCH22 Obtaining Difference Equations for Glucose Prediction by Structured Grammatical Evolution and Sparse Identification DanielParraRodriguez.html DavidJoedicke.html AlbertoGutierrez.html JoseManuelVelascoCabo.html OscarGarnica.html JManuelColmenar.html JoseIgnacioHidalgoPerez.html
28. pillay:2024:GECCOcomp Transfer Learning in Evolutionary Spaces NelishiaPillay.html
29. DBLP:conf/eurocast/PiringerWHFSA22 Improving the Flexibility of Shape-Constrained Symbolic Regression with Extended Constraints DavidPiringer.html StefanWagner.html ChristianHaider.html ArminFohler.html SiegfriedSilber.html MichaelAffenzeller.html
30. DBLP:conf/synasc/RolandKB22 Application of Symbolic Regression in Polymer Processing WolfgangRoland.html MichaelKommenda.html GeraldRomanBerger-Weber.html
31. shahrzad:telo24 EVOTER: Evolution of Transparent Explainable Rule sets HormozShahrzad.html BabakHodjat.html RistoMiikkulainen.html
32. Sipper:2021:SciRep Conservation machine learning: a case study of random forests MosheSipper.html JasonHMoore.html
33. DBLP:conf/eurocast/StroblVHKW22 Using Explainable Artificial Intelligence for Data Based Detection of Complications in Records of Patient Treatments MarinaStrobl.html JuliaVetter.html GerhardHalmerbauer.html TilmanKoenigswieser.html StephanMWinkler.html
34. Turner:2024:CACM Neural Architecture Search as Program Transformation Exploration JackTurner.html ElliotJCrowley.html MichaelFPO'Boyle.html
35. Peng_Wang:ECJ Genetic Programming for Automatically Evolving Multiple Features to Classification PengWang2.html BingXue.html JingLiang.html MengjieZhang.html

Modified

1. 1 Affenzeller:2022:GPTP Symbolic Regression in Materials Science: Discovering Interatomic Potentials from Data BogdanBurlacu.html MichaelKommenda.html GabrielKronberger.html StephanMWinkler.html MichaelAffenzeller.html
2. 2 Albinati:2014:SMGP A Study of Semantic Geometric Crossover Operators in Regression Problems JulioAlbinati.html GiseleLPappa.html FernandoEstebanBarrilOtero.html LuizOtavioVilasBoasOliveira.html
3. 1 Baltes:2020:GI9 An Annotated Dataset of Stack Overflow Post Edits SebastianBaltes.html MarkusWagner.html
4. 18 batista:2024:CEC M6GP: Multiobjective Feature Engineering JoaoEduardoBatista.html NunoMiguelRodriguesDomingos.html LeonardoVanneschi.html SaraSilva.html
5. 7 BiYing:ieeeTEC A Genetic Programming Approach with Building Block Evolving and Reusing to Image Classification YingBi.html JingLiang.html BingXue.html MengjieZhang.html
6. 1 Bokhari:2020:GI9 Genetic Improvement of Software Efficiency: The Curse of Fitness Estimation MahmoudABokhari.html MarkusWagner.html BradAlexander.html
7. 2 boldi:2023:GECCOcomp The Problem Solving Benefits of Down-Sampling Vary by Selection Scheme RyanBoldi.html AshleyBao.html MartinBriesch.html ThomasHelmuth.html DominikSobania.html LeeSpector.html AlexanderLalejini.html
8. 2 Brownlee:2023:SSBSE Enhancing Genetic Improvement Mutations Using Large Language Models AlexanderEIBrownlee.html JamesCallan.html KarineEven-Mendoza.html AlinaGeiger.html CarolHanna.html JustynaPetke.html FedericaSarro.html DominikSobania.html
9. 18 callan2023multiobjective Multi-Objective Improvement of Android Applications JamesCallan.html JustynaPetke.html
10. 1 Thesis_Alberto_Cano New Classification Models through Evolutionary Algorithms AlbertoCanoRojas.html
11. 2 Castelli:2014:SMGP The Influence of Population Size on Geometric Semantic GP MauroCastelli.html LucaManzoni.html SaraSilva.html LeonardoVanneschi.html
12. 2 Castelli:2014:SMGP2 Self-tuning Geometric Semantic GP MauroCastelli.html LucaManzoni.html SaraSilva.html LeonardoVanneschi.html
13. 1 christensen:2002:EuroGP An Analysis of Koza's Computational Effort Statistic for Genetic Programming SteffenChristensen.html FranzOppacher.html
14. 1 DBLP:journals/corr/CirilloLN14 Evolving intraday foreign exchange trading strategies utilizing multiple instruments price series SimoneCirillo.html StefanLloyd.html PeterNordin.html
15. 2 Correia:2014:SMGP Semantic Operators for Evolutionary Art JoaoNunoGoncalvesCostaCavaleiroCorreia.html PenousalMachado.html
16. 2 icga85:cramer A representation for the Adaptive Generation of Simple Sequential Programs NichaelLynnCramer.html
17. 1 cranmer2023interpretablemachinelearningscience Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl MilesCranmer.html
18. 24 DEDOMENICO:2023:prostr Machine-learning-enhanced variable-angle truss model to predict the shear capacity of RC elements with transverse reinforcement DarioDeDomenico.html GiuseppeQuaranta.html QingcongZeng.html GiorgioMonti.html
19. 4 deFranca:ieeeTEC SRBench++: Principled Benchmarking of Symbolic Regression With Domain-Expert Interpretation FabricioOlivettideFranca.html MarcoVirgolin.html MichaelKommenda.html MaimunaMajumder.html MilesCranmer.html GuilhermeJorgeNunesMonteiroEspada.html LeonIngelse.html AlcidesFonseca.html MikelLandajuela.html BrendenKylePetersen.html RubenGlatt.html TNathanMundhenk.html ChakShingLee.html JacobDeanHochhalter.html DavidLRandall.html Pierre-AlexandreKamienny.html HengzheZhang.html GrantDick.html AlessandroSimon.html BogdanBurlacu.html JaanKasak.html MeeraMachado.html CasperWilstrup.html WilliamLaCava.html
20. 1 ebner:1999:OSSGPIRNSS On the Search Space of Genetic Programming and Its Relation to Nature's Search Space MarcEbner.html
21. 1 fernando2023promptbreeder Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution ChrisanthaFernando.html DylanBanarse.html HenrykMichalewski.html SimonOsindero.html TimRocktaschel.html
22. 1 FGGD06 Learning tactical human behavior through observation of human performance HansFernlund.html AvelinoJGonzalez.html MichaelGeorgiopoulos.html RonaldFDeMara.html
23. 1 ferreira:2002:WSC Function Finding and the Creation of Numerical Constants in Gene Expression Programming CandidaFerreira.html
24. 1 DBLP:journals/corr/abs-1801-04407 Towards a more efficient representation of imputation operators in TPOT UnaiGarciarenaHualde.html AlexanderMendiburu.html RobertoSantana.html
25. 6 Gavrilis20081358 Selecting and constructing features using grammatical evolution DimitrisGavrilis.html IoannisGTsoulos.html EvangelosDermatas.html
26. 1 Gruau:1994:thesis Neural Network Synthesis using Cellular Encoding and the Genetic Algorithm FredericGruau.html
27. 5 gruau:1996:ceVdeGNN A Comparison between Cellular Encoding and Direct Encoding for Genetic Neural Networks FredericGruau.html LDarrellWhitley.html LarryDPyeatt.html
28. 1 DBLP:journals/corr/abs-2308-00672 Active Learning in Genetic Programming: Guiding Efficient Data Collection for Symbolic Regression NathanielHaut.html WolfgangBanzhaf.html WilliamFPunch.html
29. 1 He:2013:IJCAI Learning Optimal Auction Mechanism in Sponsored Search DiHe.html WeiChen.html LiweiWang.html Tie-yanLiu.html
30. 1 hemberg2024evolvingcodelargelanguage Evolving Code with A Large Language Model ErikHemberg.html StephenMoskal.html Una-MayO'Reilly.html
31. 4 Holladay:2007:icdsp Evolution of Signal Processing Algorithms using Vector Based Genetic Programming KennethLHolladay.html KayARobbins.html
32. 1 1144067 Indirect co-evolution for understanding belief in an incomplete information dynamic game NanlinJin.html
33. 1 Johnson:2014:SMGPwork Semantic Methods in Genetic Programming ColinGJohnson.html KrzysztofKrawiec.html AlbertoMoraglio.html MichaelO'Neill.html
34. 2 Johnson:2014:SMGP Information Theory, Fitness, and Sampling Semantics ColinGJohnson.html JohnRWoodward.html
35. 1 keijzer03 Improving Symbolic Regression with Interval Arithmetic and Linear Scaling MaartenKeijzer.html
36. 3 Kelly:thesis Scaling Genetic Programming to Challenging Reinforcement Tasks through Emergent Modularity StephenKelly.html
37. 2 Kocsis:2014:SMGP Asymptotic Genetic Improvement Programming via Type Functors and Catamorphisms ZoltanKocsis.html JerrySwan.html
38. 1 Koza89 Hierarchical genetic algorithms operating on populations of computer programs JohnKoza.html
39. 1 Koza:1992:GPgs Genetic evolution and co-evolution of game strategies JohnKoza.html
40. 1 Koza:1992:lizrd Evolution of food foraging strategies for the Caribbean Anolis lizard using genetic programming JohnKoza.html JamesPRice.html JonathanRoughgarden.html
41. 3 Article:91:Koza:GeneticAlgoritm A Hierarchical Approach to Learning the Boolean Multiplexer Function JohnKoza.html
42. 1 koza:book Genetic Programming: On the Programming of Computers by Means of Natural Selection JohnKoza.html
43. 11 koza:1995:gendup Gene Duplication to Enable Genetic Programming to Concurrently Evolve Both the Architecture and Work-Performing Steps of a Computer Program JohnKoza.html
44. 1 koza:1999:GPdim Genetic Programming as a Darwinian Invention Machine JohnKoza.html ForrestBennett.html OscarStiffelman.html
45. 1 DBLP:journals/corr/abs-1903-09688 Symbolic Regression Methods for Reinforcement Learning JiriKubalik.html JanZegklitz.html ErikDerner.html RobertBabuska.html
46. LaCava:2020:GECCO Genetic Programming Approaches to Learning Fair Classifiers WilliamLaCava.html JasonHMoore.html
47. 1 LaCava:2021:NeurIPS Contemporary Symbolic Regression Methods and their Relative Performance WilliamLaCava.html PatrykOrzechowski.html BogdanBurlacu.html FabricioOlivettideFranca.html MarcoVirgolin.html YingJin.html MichaelKommenda.html JasonHMoore.html
48. 1 langdon:2010:jss Efficient multi-objective higher order mutation testing with genetic programming WilliamBLangdon.html MarkHarman.html YueJia.html
49. 1 langdon:2019:GPEM Genetic Programming and Evolvable Machines at 20 WilliamBLangdon.html
50. 1 langdon:2020:GI9 Evolving sqrt into 1/x via Software Data Maintenance WilliamBLangdon.html OliverKrauss.html
51. 3 Liu:2010:ieeeTSE Evolutionary Optimization of Software Quality Modeling with Multiple Repositories YiLiu.html TaghiMKhoshgoftaar.html JimSeliya.html
52. 1 luke:dissertation Issues in Scaling Genetic Programming: Breeding Strategies, Tree Generation, and Code Bloat SeanLuke.html
53. 1 Lundh:2007:GPEM Cellular Automaton Modeling of Biological Pattern Formation: Characterization, Applications, and Analysis Authors: Andreas Deutsch and Sabine Dormann, Birkhauser, 2005, XXVI, 334 p., 131 illus., Hardcover. ISBN:0-8176-4281-1, List Price: \$89.95 TorbjornLundh.html
54. 1 mahboub:tel-00696675 Emotional processes modelling in decision making KarimMahboub.html
55. 2 Mambrini:2014:SMGP A framework for measuring the generalization ability of Geometric Semantic Genetic Programming (GSGP) for Black-Box Boolean Functions Learning AndreaMambrini.html YangYu2.html XinYao.html
56. 1 Marginean_10137954_thesis_redacted Automated Software Transplantation AlexandruMarginean.html
57. 1 journals/ijimai/MartinQI21 Dynamic Generation of Investment Recommendations Using Grammatical Evolution CarlosMartin.html DavidQuintanaMontero.html PedroIsasiVinuela.html
58. 2 Martinez:2016:GPEM Prediction of expected performance for a genetic programming classifier YulianaMartinez.html LeonardoTrujillo.html PierrickLegrand.html EdgarGalvanLopez.html
59. 1 journals/jetai/MartinezNTLL17 A comparison of fitness-case sampling methods for genetic programming YulianaMartinez.html EnriqueNaredo.html LeonardoTrujillo.html PierrickLegrand.html UrielLopez.html
60. 2 Moraglio:2014:SMGP Geometric Semantic Grammatical Evolution AlbertoMoraglio.html JamesMcDermott.html MichaelO'Neill.html
61. 2 Moraglio:2014:SMGP2 An Efficient Implementation of GSGP using Higher-Order Functions and Memoization AlbertoMoraglio.html
62. 3 Mosayebi:2020:GI9 Tuning Genetic Algorithm Parameters using Design of Experiments MohsenMosayebi.html ManbirSSodhi.html
63. 1 Moscato:2020:superconductor Learning to extrapolate using continued fractions: Predicting the critical temperature of superconductor materials PabloMoscato.html MohammadNazmulHaque.html KevinHuang.html JuliaSloan.html JonCdeOliveira.html
64. 2 murphy:2023:GEWS2023 Initialisation in Structured Grammatical Evolution AidanMurphy.html NunoLourenco.html AnthonyVentresque.html
65. 3 Patelli:2011:ICAC A regressive schema theory based tool for GP evolved nonlinear models AlinaPatelli.html LaviniaFerariu.html
66. 2 Pawlak:2014:SMGP Guarantees of Progress for Geometric Semantic Genetic Programming TomaszPawlak.html KrzysztofKrawiec.html
67. 2 Pinna:2024:EuroGP Enhancing Large Language Models-Based Code Generation by Leveraging Genetic Improvement GiovanniPinna.html DamianoRavalico.html LuigiRovito.html LucaManzoni.html AndreaDeLorenzo.html
68. 1 Poli:1999:nio Parallel Distributed Genetic Programming RiccardoPoli.html
69. 1 radwan2024comparisonrecentalgorithmssymbolic A Comparison of Recent Algorithms for Symbolic Regression to Genetic Programming YousefARadwan.html GabrielKronberger.html StephanMWinkler.html
70. 22 raghav:2024:GECCOcomp Interactive Symbolic Regression - A Study on Noise Sensitivity and Extrapolation Accuracy SSanjithRaghav.html STejeshKumar.html RishiikeshBalaji.html MSanjay.html CShunmugaVelayutham.html
71. 2 ramos-criado:ECJ Estimation of Distribution Algorithm for Grammar-Guided Genetic Programming PabloRamosCriado.html DoloresBarriosRolania.html DaviddelaHozGaliana.html DanielManriqueGamo.html
72. 20 RAZAVI:2019:AE A practical feature-engineering framework for electricity theft detection in smart grids RouzbehRazavi.html AminGharipour.html MartinFleury.html IkpeJusticeAkpan.html
73. 1 Reid:2020:GI9 Optimising the Fit of Stack Overflow Code Snippets into Existing Code BrittanyReid.html ChristophTreude.html MarkusWagner.html
74. 1 Renzullo:2018:GI Neutrality and Epistasis in Program Space JosephRenzullo.html WestleyWeimer.html MelanieMoses.html StephanieForrest.html
75. 7 ribeiro:2023:EPIA A Novel Federated Learning Approach to Enable Distributed and Collaborative Genetic Programming BrunoRibeiro.html LuisGomes.html ZitaVale.html
76. 5 Ribeiro:2023:GPTP TPOT2: A New Graph-Based Implementation of the Tree-Based Pipeline Optimization Tool for Automated Machine Learning PedroRibeiroMendesJunior.html AnilKumarSaini.html JayMoran.html NicholasMatsumoto.html HyunjunChoi.html MiguelEHernandez.html JasonHMoore.html
77. 17 Ruiz-Ortega:2024:SciRep An evolutionary parsimonious approach to estimate daily reference evapotranspiration FranciscoJavierRuizOrtega.html EddieHelbertClementeTorres.html AliciaMartinezRebollar.html JoseJassonFloresPrieto.html
78. 1 ryan:1998:geepal Grammatical Evolution: Evolving Programs for an Arbitrary Language ConorRyan.html JohnJamesCollins.html MichaelO'Neill.html
79. 5 Sabar:2018:GECCO A genetic programming based iterated local search for software project scheduling NasserRSabar.html AyadMashaanTurky.html AndySong.html
80. 20 Sanchez:2017:ROPEC Semantic genetic operators based on a selection mechanism tailored for the root function ClaudiaNallelySanchezGomez.html MarioGraffGuerrero.html
81. 1 Schmidt:2009:rebuttal A Rebuttal to Christopher Hillar and Friedrich Sommer's Comment on Distilling Laws from Data MichaelDSchmidt.html HodLipson.html
82. 1 schulte2014dissertation Neutral Networks of Real-World Programs and their Application to Automated Software Evolution EricSchulte.html
83. 5 Shali:2007:ICMLA Using genetic programming for the induction of oblique decision trees AminShali.html MohammadRezaKangavari.html BaharehBina.html
84. 1 ShetaAfeef2010 Software Effort Estimation for NASA Projects Using Genetic Programming AlaaSheta.html AlaaAl-Afeef.html
85. 25 SHIRANIFARADONBEH:2024:AAIMGE Chapter 12 - Application of artificial intelligence in distinguishing genuine microseismic events from the noise signals in underground mines RoohollahShiraniFaradonbeh.html MuhammadGhiffariRyoza.html MohammadaliSepehri.html
86. 1 DissertationKonradSickel Computerized Automatic Modeling of Medical Prostheses KonradSickel.html
87. 1 Sipper2019tinyGP Tiny Genetic Programming in Python MosheSipper.html
88. 1 Sourbier:thesis Learning-based Intrusion Detection: An imbalanced, constantly evolving and Timely Problem NicolasSourbier.html
89. 7 Souza:TOSEM Software Product Line Engineering via Software Transplantation LeandroOliveiradeSouza.html EduardoSantanadeAlmeida.html PauloAnselmodaMotaSilveiraNeto.html EarlBarr.html JustynaPetke.html
90. 2 push2-description Push 2.0 Programming Language Description LeeSpector.html ChristopherHPerry.html JonKlein.html
91. 2 Swan:2014:SMGP Semantically-meaningful Numeric Constants for Genetic Programming JerrySwan.html JohnHDrake.html KrzysztofKrawiec.html
92. 2 swan:2014:SMGP2 Analysis of Semantic Building Blocks via Groebner Bases JerrySwan.html GeoffreyKNeumann.html KrzysztofKrawiec.html
93. 22 thi:2022:AIC Cartesian Genetic Programming: Some New Detections ThuongPhamThi.html
94. 1 Vanneschi:book Lectures on Intelligent Systems LeonardoVanneschi.html SaraSilva.html
95. 1 VanVeldhuizen:thesis Multiobjective Evolutionary Algorithms: Classification, Analysis, and New Innovations DavidAVanVeldhuizen.html
96. 5 Vassilev:thesis Fitness landscapes and search in the evolutionary design of digital circuits VesselinKVassilev.html
97. 1 wang:2024:CEC Dimensionality Reduction for Classification Using Divide-and-Conquer Based Genetic Programming PengWang2.html BingXue.html JingLiang.html MengjieZhang.html
98. 2 White:2019:GPTP Modelling Genetic Programming as a Simple Sampling Algorithm DavidRobertWhite.html BenjaminFowler.html WolfgangBanzhaf.html EarlBarr.html
99. 6 Meng_Xu:ieeeTEC Genetic Programming with Lexicase Selection for Large-scale Dynamic Flexible Job Shop Scheduling MengXu.html YiMei.html FangfangZhang.html MengjieZhang.html
100. 5 Zhang:ieeeTEC2 SR-Forest: A Genetic Programming based Heterogeneous Ensemble Learning Method HengzheZhang.html AiminZhou.html QiChen.html BingXue.html MengjieZhang.html
101. 8 Hengzhe_Zhang:ieeeTEC Modular Multi-Tree Genetic Programming for Evolutionary Feature Construction for Regression HengzheZhang.html QiChen.html BingXue.html WolfgangBanzhaf.html MengjieZhang.html

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