Changes to Genetic Programing Bibliography since 2024/11/01

New

1. Abdollahzadeh:2016:CC Predicting of compressive strength of recycled aggregate concrete by genetic programming GholamrezaAbdollahzadeh.html EhsanJahani.html ZahraKashir.html
2. Abdulkarimova:2025:GPEM Harnessing evolutionary algorithms for enhanced characterization of ENSO events UlviyaAbdulkarimova.html RodrigoAbarcaDelRio.html PierreCollet.html
3. 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
4. Babic:2024:sv-jme Selective Laser Melting: A Novel Method for Surface Roughness Analysis MatejBabic.html MihaKovacic.html CristianoFragassa.html RomanSturm.html
5. boldi2022environmentaldiscontinuityhypothesisdownsampled The Environmental Discontinuity Hypothesis for Down-Sampled Lexicase Selection RyanBoldi.html ThomasHelmuth.html LeeSpector.html
6. 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
7. 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
8. Callan:2025:ASE Multi-objective improvement of Android applications JamesCallan.html JustynaPetke.html
9. Cano:2025:GPEM Hardware real-time individualised blood glucose predictor generator based on grammars and cartesian genetic programming JorgeCano.html JoseIgnacioHidalgoPerez.html OscarGarnica.html
10. Chavan:2013:IJERA Shear Strength of Slender Reinforced Concrete Beams without Web Reinforcement RSChavan.html PrashantMPawar.html
11. 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
12. Degtyarev:2022:SCS Design models for predicting shear resistance of studs in solid concrete slabs based on symbolic regression with genetic programming VitaliyVDegtyarev.html StephenJHicks.html JeromeFHajjar.html
13. ding:2022:LEOL Lexicase Selection at Scale LiDing.html RyanBoldi.html ThomasHelmuth.html LeeSpector.html
14. Dolson:2018:PeerJ Ecological theory provides insights about evolutionary computation EmilyDolson.html WolfgangBanzhaf.html CharlesOfria.html
15. Dolson_grad.msu_0128D_16624 On the constructive power of ecology in open-ended evolving systems EmilyDolson.html
16. Dong:ieeeTEC Evolving Equation Learner For Symbolic Regression JunlanDong.html JinghuiZhong.html WeiliLiu.html JunZhang.html
17. El-Baroudy:2008:hydropredict Identification and Quantification of the Soil Moisture Response to the Atmospheric Forcing IbrahimEl-Baroudy.html AminElshorbagy.html
18. Garg:2020:IJER Aging model development based on multidisciplinary parameters for lithium-ion batteries AkhilGarg.html ShaosenSu.html LiangGao.html XiongbinPeng.html PrashantBaredar.html
19. GilGala:2024:AI Evolving routing policies for electric vehicles by means of genetic programming FranciscoJavierGilGala.html MarkoDurasevic.html DomagojJakobovic.html
20. DBLP:conf/eurocast/HaiderK22 Shape-Constrained Symbolic Regression with NSGA-III ChristianHaider.html GabrielKronberger.html
21. Haut:ieeeTEC Active Learning in Genetic Programming: Guiding Efficient Data Collection for Symbolic Regression NathanielHaut.html WolfgangBanzhaf.html WilliamFPunch.html
22. Kalkreuth:2024:sigevolution Drifting and Evolving: The graph-based Genetic Programming community has entered a new Era RomanTobiasKalkreuth.html
23. DBLP:conf/eurocast/KammererKK22 Symbolic Regression with Fast Function Extraction and Nonlinear Least Squares Optimization LukasKammerer.html GabrielKronberger.html MichaelKommenda.html
24. Kocherovsky:2024:ALife Crossover Destructiveness in Cartesian versus Linear Genetic Programming MarkKocherovsky.html WolfgangBanzhaf.html
25. langdon:2024:ASE Deep Imperative Mutations have Less Impact WilliamBLangdon.html DavidClark.html
26. Larkin:thesis Artificial Evolution Approaches to Address the Data Challenges Encountered During Financial Forecasting FiaccLarkin.html
27. 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
28. Mahdinejad:thesis Optimizing Convolutional Neural Network Segmentation Tasks Using Evolutionary Algorithms MahsaMahdinejad.html
29. Minns:thesis Artificial Neural Networks as Subsymbolic Process Descriptors AnthonyWMinns.html
30. Murphy:2024:GPEM An investigation into structured grammatical evolution initialisation AidanMurphy.html MahsaMahdinejad.html AnthonyVentresque.html NunoLourenco.html
31. DBLP:journals/cma/MuszynskiVBSK12 Convergence analysis of evolutionary algorithms in the presence of crash-faults and cheaters JakubMuszynski.html SebastienVarrette.html PascalBouvry.html FranciszekSeredynski.html SameeUllahKhan.html
32. Nemeth:2024:ALife Phenotypic Species Definitions for Genetic Improvement of Source Code ZsoltNemeth.html PenelopeFaulknerRainford.html BarryPorter.html
33. Ochoa:2024:sigevolution The 2024 ACM SIGEVO Outstanding Contribution Awardees: Prof. Dr. Franz Rothlauf, Information Systems, University of Mainz, Germany GabrielaOchoa.html
34. 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
35. 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
36. DBLP:conf/synasc/RolandKB22 Application of Symbolic Regression in Polymer Processing WolfgangRoland.html MichaelKommenda.html GeraldRomanBerger-Weber.html
37. Rosenfeld:2025:GPEM A survey on batch training in genetic programming LiahRosenfeld.html LeonardoVanneschi.html
38. Santos:thesis Adaptacao de algoritmos hibridos baseados em aprendizagem de maquinas para aplicacao em problemas na area de Saude com bases de dados desbalanceadas LaercioIvesSantos.html
39. shahrzad:telo24 EVOTER: Evolution of Transparent Explainable Rule sets HormozShahrzad.html BabakHodjat.html RistoMiikkulainen.html
40. DBLP:conf/aaaifs/SpectorKP04 Tags and the Evolution of Cooperation in Complex Environments LeeSpector.html JonKlein.html ChristopherHPerry.html
41. 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
42. Syed:thesis Data driven modelling for environmental water management MofazzalHaiderSyed.html
43. Turner:2024:CACM Neural Architecture Search as Program Transformation Exploration JackTurner.html ElliotJCrowley.html MichaelFPO'Boyle.html
44. Vroomans:2025:GPEM Review: ``Computational evolution of neural and morphological development'', Yaochu Jin, ISBN 978-981-99-1853-9, Springer, 2023 RenskeVroomans.html
45. Peng_Wang:ECJ Genetic Programming for Automatically Evolving Multiple Features to Classification PengWang2.html BingXue.html JingLiang.html MengjieZhang.html
46. idea_3422_OBJ On the interplay of architecture and collaboration on software evolution and maintenance SunnyWong.html

Modified

1. 1 abdulkarimova:2019:ajhpc The PARSEC machine: a non-Newtonian supra-linear super-computer UlviyaAbdulkarimova.html AnnaOuskovaLeonteva.html ChristianRolando.html AnneJeannin-Girardon.html PierreCollet.html
2. 1 Affenzeller:2022:GPTP Symbolic Regression in Materials Science: Discovering Interatomic Potentials from Data BogdanBurlacu.html MichaelKommenda.html GabrielKronberger.html StephanMWinkler.html MichaelAffenzeller.html
3. 1 Afzal2009 A systematic review of search-based testing for non-functional system properties WasifAfzal.html RichardTorkar.html RobertFeldt.html
4. 4 Ahluwalia:2001:SA Coevolving functions in genetic programming ManuAhluwalia.html LarryBull.html
5. 1 ahmed:2020:IJDC A novel genetic-programming based differential braking controller for an 8x8 combat vehicle MoatazAhmed.html MoustafaEl-Gindy.html HaoxiangLang.html
6. 2 Albinati:2014:SMGP A Study of Semantic Geometric Crossover Operators in Regression Problems JulioAlbinati.html GiseleLPappa.html FernandoEstebanBarrilOtero.html LuizOtavioVilasBoasOliveira.html
7. 1 Ali:thesis Intelligent Decision Making Ensemble Classification System for Breast Cancer Prediction SafdarAli.html
8. 3 Antonelli:2013:NAFIPS Evolutionary Fuzzy Classifiers for Imbalanced Datasets: An Experimental Comparison MichelaAntonelli.html PietroDucange.html FrancescoMarcelloni.html ArmandoSegatori.html
9. 2 Azad:2014:EC A Simple Approach to Lifetime Learning in Genetic Programming based Symbolic Regression RMuhammadAtifAzad.html ConorRyan.html
10. 29 Babu:2023:ICAEECI OCR-Based Multi-class Classification of Hate Speech in Images NithishBabuM.html PreethiP.html
11. 1 Bakurov:thesis Soft computing for Ill Posed Problems in Computer Vision IllyaBakurov.html
12. 1 Bakurov:2024:GPEM Geometric semantic genetic programming with normalized and standardized random programs IllyaBakurov.html JoseManuelMunozContreras.html MauroCastelli.html NunoMiguelRodriguesDomingos.html SaraSilva.html LeonardoTrujillo.html LeonardoVanneschi.html
13. 1 Baltes:2020:GI9 An Annotated Dataset of Stack Overflow Post Edits SebastianBaltes.html MarkusWagner.html
14. 2 Banzhaf:2024:GPEM ``The physics of evolution'' by Michael W. Roth, CRC press, 2023 WolfgangBanzhaf.html
15. 1 Batenkov:2010:HIG:1836543.1836558 Hands-on introduction to genetic programming DmitryBatenkov.html
16. 1 Batista:mastersthesis Studying elements of genetic programming for multiclass classification JoaoEBatista.html
17. 1 Batot:2022:SSM Promoting social diversity for the automated learning of complex MDE artifacts EdouardBatot.html HouariSahraoui.html
18. 2 benabdallah:2023:AJSE Active Contour Extension Basing on Haralick Texture Features, Multi-gene Genetic Programming, and Block Matching to Segment Thyroid in 3D Ultrasound Images FatmaZohraBenabdallah.html LeilaDjerou.html
19. 7 BiYing:ieeeTEC A Genetic Programming Approach with Building Block Evolving and Reusing to Image Classification YingBi.html JingLiang.html BingXue.html MengjieZhang.html
20. 1 Blot:2024:GI Automated Software Performance Improvement with Magpie AymericBlot.html
21. 1 Bokhari:2020:GI9 Genetic Improvement of Software Efficiency: The Curse of Fitness Estimation MahmoudABokhari.html MarkusWagner.html BradAlexander.html
22. 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
23. 3 SAND2005-0014 Graduated Embodiment for Sophisticated Agent Evolution and Optimization MarkBoslough.html MichaelDPeters.html ArthurinePierson.html
24. 1 Buccheri:2024:JPT Appendicular Skeletal Muscle Mass in Older Adults Can Be Estimated With a Simple Equation Using a Few Zero-Cost Variables EnricoBuccheri.html DanieleDell'Aquila.html MarcoRusso.html RitaChiaramonte.html MicheleVecchio.html
25. 23 cano:2023:GECCOcomp Hardware Design of a Model Generator Based on Grammars and Cartesian Genetic Programming for Blood Glucose Prediction JorgeCano.html JoseIgnacioHidalgoPerez.html OscarGarnica.html JLanchares.html
26. 1 PhD_Thesis_Liwei_Cao_revised_version Combining artificial intelligence and robotic system in chemical product/process design LiweiCao.html
27. 2 Card:2008:GPTP An Application of Information Theoretic Selection to Evolution of Models with Continuous-valued Inputs StuCard.html ChilukuriKMohan.html
28. 2 Castelli:2014:SMGP The Influence of Population Size on Geometric Semantic GP MauroCastelli.html LucaManzoni.html SaraSilva.html LeonardoVanneschi.html
29. 2 Castelli:2014:SMGP2 Self-tuning Geometric Semantic GP MauroCastelli.html LucaManzoni.html SaraSilva.html LeonardoVanneschi.html
30. 1 chen:2022:FC Orientation Design and Research of Heavy Bamboo Substrate Considering Genetic Programming and Artificial Intelligence Algorithm WeiChen2.html
31. 4 Chennupati:thesis Grammatical Evolution + Multi-Cores = Automatic Parallel Programming! GopinathChennupati.html
32. 1 DBLP:journals/corr/CirilloLN14 Evolving intraday foreign exchange trading strategies utilizing multiple instruments price series SimoneCirillo.html StefanLloyd.html PeterNordin.html
33. 3 Cohen:2023:GI It's all in the Semantics: When are Genetically Improved Programs Still Correct? MyraBCohen.html
34. 2 Correia:2014:SMGP Semantic Operators for Evolutionary Art JoaoNunoGoncalvesCostaCavaleiroCorreia.html PenousalMachado.html
35. 1 cranmer2023interpretablemachinelearningscience Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl MilesCranmer.html
36. 1 Creevey:2023:SciRep GASP: a genetic algorithm for state preparation on quantum computers FloydMCreevey.html CharlesDHill.html LloydCLHollenberg.html
37. 1 Custode:2023:ASC Multi-objective automatic analysis of lung ultrasound data from COVID-19 patients by means of deep learning and decision trees LeonardoLucioCustode.html FedericoMento.html FrancescoTursi.html AndreaSmargiassi.html RiccardoInchingolo.html TizianoPerrone.html LibertarioDemi.html GiovanniIacca.html
38. 1 Angan:Das:thesis Algorithms for Topology Synthesis of Analog Circuits AnganDas.html
39. 18 Das:2009:DATE A graph grammar based approach to automated multi-objective analog circuit design AnganDas.html RangaVemuri.html
40. 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
41. 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
42. 26 conf/eurogp/DoucetteH08 GP Classification under Imbalanced Data sets: Active Sub-sampling and AUC Approximation JohnADoucette.html MalcolmHeywood.html
43. 1 FAN:2024:knosys A genetic programming-based method for image classification with small training data QinglanFan.html YingBi.html BingXue.html MengjieZhang.html
44. 1 Farinati:2024:evoapplications GM4OS: An Evolutionary Oversampling Approach for Imbalanced Binary Classification Tasks DavideFarinati.html LeonardoVanneschi.html
45. 2 Farinati:2024:GPEM A survey on dynamic populations in bio-inspired algorithms DavideFarinati.html LeonardoVanneschi.html
46. 1 Fei:2015:MPM Analysis of students perceptions of seafaring career in China based on artificial neural network and genetic programming JiangangFei.html Jian-JunLu.html
47. 1 pmlr-v238-sen-fong24a Multi-Level Symbolic Regression: Function Structure Learning for Multi-Level Data KeiSenFong.html MehulMotani.html
48. 1 Fontbonne:2022:EuroGP Cooperative Co-Evolution and Adaptive Team Composition for a Multi-Rover Resources Allocation Problem NicolasFontbonne.html NicolasMaudet.html NicolasBredeche.html
49. 1 Fredericks:2023:GI Generative Art via Grammatical Evolution ErikMFredericks.html AbigailCDiller.html JaredMMoore.html
50. 1 DBLP:journals/corr/abs-1801-04407 Towards a more efficient representation of imputation operators in TPOT UnaiGarciarenaHualde.html AlexanderMendiburu.html RobertoSantana.html
51. 10 gearhart:2003:GPPSMDP Genetic Programming as Policy Search in Markov Decision Processes ChrisGearhart.html
52. 1 Goebel:thesis Towards reliable characterization and model-based evaluation of organic solvent nanofiltration RebeccaGoebel.html
53. 1 gold:2022:GPTP GUI-Based, Efficient Genetic Programming and AI Planning for Unity3D RobertGold.html AndrewHaydnGrant.html ErikHemberg.html ChathikaSGunaratne.html Una-MayO'Reilly.html
54. 2 Goschen:2022:CEC Genetic Micro-Programs for Automated Software Testing with Large Path Coverage JarrodGoschen.html AnnaSBosman.html StefanGruner.html
55. 5 gruau:1996:ceVdeGNN A Comparison between Cellular Encoding and Direct Encoding for Genetic Neural Networks FredericGruau.html LDarrellWhitley.html LarryDPyeatt.html
56. 1 Gu:thesis Static and Dynamic Analysis of Nonlinear Valve Springs Based on Finite Element Analysis and Machine Learning Algorithm ZewenGu.html
57. 1 Hamilton:2023:evoapplications Predicting Normal and Anomalous Urban Traffic with Vectorial Genetic Programming and Transfer Learning JohnConnorRegoHamilton.html AnikoEkart.html AlinaPatelli.html
58. 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
59. 1 Heaton:GPEM:deep_learning Ian Goodfellow, Yoshua Bengio, and Aaron Courville: Deep learning JeffHeaton.html
60. 1 hemberg2024evolvingcodelargelanguage Evolving Code with A Large Language Model ErikHemberg.html StephenMoskal.html Una-MayO'Reilly.html
61. 2 Hemberg:2024:GPEM Evolving code with a large language model ErikHemberg.html StephenMoskal.html Una-MayO'Reilly.html
62. 1 Hidalgo:2023:GPTP Genetic Programming Techniques for Glucose Prediction in People with Diabetes JoseIgnacioHidalgoPerez.html JoseManuelVelascoCabo.html DanielParraRodriguez.html OscarGarnica.html
63. 25 Hsu20122933 Improving the lighting performance of a 3535 packaged hi-power LED using genetic programming, quality loss functions and particle swarm optimization Chih-MingHsu.html
64. 2 Hu:2022:GPTP Genetic Programming for Interpretable and Explainable Machine Learning TingHu.html
65. 1 Hussain:2023:GPTP Let's Evolve Intelligence, Not Solutions TalibSHussain.html
66. 2 iba:1997:malrntGP Multiple-Agent Learning for a Robot Navigation Task by Genetic Programming HitoshiIba.html
67. 1 Islam:alife22 String: a programming language for the evolution of ribozymes in a new computational protocell model MohiulIslam.html NawwafKharma.html PeterGrogono.html
68. 2 Johanson98 GP-Music: An Interactive Genetic Programming System for Music Generation with Automated Fitness Raters BradleyEJohanson.html RiccardoPoli.html
69. 1 Johnson:2014:SMGPwork Semantic Methods in Genetic Programming ColinGJohnson.html KrzysztofKrawiec.html AlbertoMoraglio.html MichaelO'Neill.html
70. 2 Johnson:2014:SMGP Information Theory, Fitness, and Sampling Semantics ColinGJohnson.html JohnRWoodward.html
71. 1 keijzer03 Improving Symbolic Regression with Interval Arithmetic and Linear Scaling MaartenKeijzer.html
72. 1 khan:evoANNdev Evolution of Artificial Neural Development: In search of learning genes GulMuhammadKhan.html
73. 1 Khandelwal:book Automating Data-Driven Modelling of Dynamical Systems: An Evolutionary Computation Approach DhruvKhandelwal.html
74. 2 Kocsis:2014:SMGP Asymptotic Genetic Improvement Programming via Type Functors and Catamorphisms ZoltanKocsis.html JerrySwan.html
75. 1 Kosorukov:2024:ASENIER Mining for Mutation Operators for Reduction of Information Flow Control Violations IlyaKosorukov.html DanielBlackwell.html DavidClark.html MyraBCohen.html JustynaPetke.html
76. 1 Koza89 Hierarchical genetic algorithms operating on populations of computer programs JohnKoza.html
77. 3 Article:91:Koza:GeneticAlgoritm A Hierarchical Approach to Learning the Boolean Multiplexer Function JohnKoza.html
78. 1 koza:book Genetic Programming: On the Programming of Computers by Means of Natural Selection JohnKoza.html
79. 1 DBLP:journals/corr/abs-1903-09688 Symbolic Regression Methods for Reinforcement Learning JiriKubalik.html JanZegklitz.html ErikDerner.html RobertBabuska.html
80. 2 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
81. 2 langdon:2008:CES-481 Genetic Programming for Drug Discovery WilliamBLangdon.html
82. 1 langdon:2020:GI9 Evolving sqrt into 1/x via Software Data Maintenance WilliamBLangdon.html OliverKrauss.html
83. 2 langdon:2024:sigevolution Searching the Genetic Programming Bibliography WilliamBLangdon.html
84. 2 Langdon:2024:EI Sustaining Evolution for Shallow Embodied Intelligence WilliamBLangdon.html DanielHulme.html
85. 1 conf/eurogp/LarkinR08 Good News: Using News Feeds with Genetic Programming to Predict Stock Prices FiaccLarkin.html ConorRyan.html
86. 1 Lehman:2023:GPTP The OpenELM Library: Leveraging Progress in Language Models for Novel Evolutionary Algorithms HerbieBradley.html HongluFan.html TheodorosGalanos.html RyanZhou.html DanielScott.html JoelLehman.html
87. 1 Liou:2022:IISWC Understanding the Power of Evolutionary Computation for GPU Code Optimization Jhe-YuLiou.html MuaazGulAwan.html StevenAHofmeyr.html StephanieForrest.html Carole-JeanWu.html
88. 2 Lorway:2021:AIMC Autopia: An AI collaborator for live networked computer music performance NorahLorway.html EdwardPowley.html ArthurWilson.html
89. 1 Lu:2022:RemoteSensing Genetic Programming for High-Level Feature Learning in Crop Classification MiaoLu.html YingBi.html BingXue.html QiongHu.html MengjieZhang.html YanbingWei.html PengYang.html WenbinWu.html
90. 1 luke:dissertation Issues in Scaling Genetic Programming: Breeding Strategies, Tree Generation, and Code Bloat SeanLuke.html
91. 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
92. 1 Machado:2022:GPTP GP-Based Generative Adversarial Models PenousalMachado.html FranciscoBaeta.html TiagoMartins.html JoaoNunoGoncalvesCostaCavaleiroCorreia.html
93. 2 ijcai2024coin From Pixels to Metal: AI-Empowered Numismatic Art PenousalMachado.html TiagoMartins.html JoaoNunoGoncalvesCostaCavaleiroCorreia.html LuisEspiritoSanto.html NunoLourenco.html JoaoMiguelCunha.html SergioMRebelo.html PedroMartins.html JoaoBicker.html
94. 38 Maheta:2015:ICCCI Classification of imbalanced data sets using Multi Objective Genetic Programming HardikHMaheta.html VipulKDabhi.html
95. 2 Maldonado:GPEM GSGP-hardware: instantaneous symbolic regression with an FPGA implementation of geometric semantic genetic programming YazminMaldonadoRobles.html RubenDarioSalasVillegas.html JoelAntonioQuevedoFelix.html RogelioValdez.html LeonardoTrujillo.html
96. 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
97. 1 DBLP:journals/bmcbi/ManduchiFRRM20 Embedding covariate adjustments in tree-based automated machine learning for biomedical big data analyses ElisabettaManduchi.html WeixuanFu.html JosephDRomano.html StefanoRuberto.html JasonHMoore.html
98. 1 Marginean_10137954_thesis_redacted Automated Software Transplantation AlexandruMarginean.html
99. 1 journals/ijimai/MartinQI21 Dynamic Generation of Investment Recommendations Using Grammatical Evolution CarlosMartin.html DavidQuintanaMontero.html PedroIsasiVinuela.html
100. 2 Martinez:2016:GPEM Prediction of expected performance for a genetic programming classifier YulianaMartinez.html LeonardoTrujillo.html PierrickLegrand.html EdgarGalvanLopez.html
101. 1 journals/jetai/MartinezNTLL17 A comparison of fitness-case sampling methods for genetic programming YulianaMartinez.html EnriqueNaredo.html LeonardoTrujillo.html PierrickLegrand.html UrielLopez.html
102. 1 Maslyaev:2023:GECCOcomp Comparison of Single- and Multi- Objective Optimization Quality for Evolutionary Equation Discovery MikhailAMaslyaev.html AlexanderAHvatov.html
103. 2 mckayabbass01:rtqrt Anticorrelation Measures in Genetic Programming RI_Bob_McKay.html HusseinAAbbass.html
104. 2 Moraglio:2014:SMGP Geometric Semantic Grammatical Evolution AlbertoMoraglio.html JamesMcDermott.html MichaelO'Neill.html
105. 2 Moraglio:2014:SMGP2 An Efficient Implementation of GSGP using Higher-Order Functions and Memoization AlbertoMoraglio.html
106. 3 Mosayebi:2020:GI9 Tuning Genetic Algorithm Parameters using Design of Experiments MohsenMosayebi.html ManbirSSodhi.html
107. 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
108. 2 murphy:2023:GEWS2023 Initialisation in Structured Grammatical Evolution AidanMurphy.html NunoLourenco.html AnthonyVentresque.html
109. 2 murphy-thesis Manipulating Convergence In Evolutionary Systems GearoidMurphy.html
110. 1 nadizar:2024:TELO An Analysis of the Ingredients for Learning Interpretable Symbolic Regression Models with Human-in-the-loop and Genetic Programming GiorgiaNadizar.html LuigiRovito.html AndreaDeLorenzo.html EricMedvet.html MarcoVirgolin.html
111. 1 Nilsen:2023:GPEM Reward tampering and evolutionary computation: a study of concrete AI-safety problems using evolutionary algorithms MathiasKNilsen.html TonnesFNygaard.html KaiOlavEllefsen.html
112. 5 Ombuki-Berman:2024:GPEM Leonardo Vanneschi and Sara Silva: lectures on intelligent systems BeatriceOmbuki-Berman.html
113. 35 PATILSHINDE:2018:Calphad Genetic programming based models for prediction of vapor-liquid equilibrium VeenaPatil-Shinde.html SanjeevSTambe.html
114. 2 Pawlak:2014:SMGP Guarantees of Progress for Geometric Semantic Genetic Programming TomaszPawlak.html KrzysztofKrawiec.html
115. 1 Petke:2023:ESE Program transformation landscapes for automated program modification using Gin JustynaPetke.html BradAlexander.html EarlBarr.html AlexanderEIBrownlee.html MarkusWagner.html DavidRobertWhite.html
116. 1 Poli:1999:nio Parallel Distributed Genetic Programming RiccardoPoli.html
117. 2 Prince:2021:evoapplications A Multi-Objective Evolutionary Algorithm Approach for Optimizing Part Quality Aware Assembly Job Shop Scheduling Problems MichaelHPrince.html KristianKDeHaan.html DanielRTauritz.html
118. 1 Quiroz:2017:IJCA Interactive Shape Perturbation JuanCQuiroz.html SergiuMDascalu.html
119. 1 radwan2024comparisonrecentalgorithmssymbolic A Comparison of Recent Algorithms for Symbolic Regression to Genetic Programming YousefARadwan.html GabrielKronberger.html StephanMWinkler.html
120. 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
121. 2 ramos-criado:ECJ Estimation of Distribution Algorithm for Grammar-Guided Genetic Programming PabloRamosCriado.html DoloresBarriosRolania.html DaviddelaHozGaliana.html DanielManriqueGamo.html
122. 20 RAZAVI:2019:AE A practical feature-engineering framework for electricity theft detection in smart grids RouzbehRazavi.html AminGharipour.html MartinFleury.html IkpeJusticeAkpan.html
123. 1 Reid:2020:GI9 Optimising the Fit of Stack Overflow Code Snippets into Existing Code BrittanyReid.html ChristophTreude.html MarkusWagner.html
124. 1 Renzullo:2018:GI Neutrality and Epistasis in Program Space JosephRenzullo.html WestleyWeimer.html MelanieMoses.html StephanieForrest.html
125. 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
126. 1 rosca:thesis Hierarchical Learning with Procedural Abstraction Mechanisms JustinianRosca.html
127. 3 Rowe:2024:GPEM Benjamin Doerr and Frank Neumann (editors): theory of evolutionary computation JonathanERowe.html
128. 5 Sabar:2018:GECCO A genetic programming based iterated local search for software project scheduling NasserRSabar.html AyadMashaanTurky.html AndySong.html
129. 2 DBLP:phd/dnb/Salustowicz03 Probabilistic Incremental Program Evolution RafalSalustowicz.html
130. 34 SANTOS:2022:ESA Decision tree and artificial immune systems for stroke prediction in imbalanced data LaercioIvesSantos.html MuriloOsorioCamargos.html MarcosFlavioSilveiraVasconcelosD'Angelo.html JoaoBatistaMendes.html EgydioEmilianoCamargosdeMedeiros.html AndreLuizSenaGuimaraes.html ReinaldoMartinezPalhares.html
131. 1 Science09:Schmidt Distilling Free-Form Natural Laws from Experimental Data MichaelDSchmidt.html HodLipson.html
132. 1 Schmidt:2009:rebuttal A Rebuttal to Christopher Hillar and Friedrich Sommer's Comment on Distilling Laws from Data MichaelDSchmidt.html HodLipson.html
133. 1 schulte2014dissertation Neutral Networks of Real-World Programs and their Application to Automated Software Evolution EricSchulte.html
134. 1 Sheneman:thesis The evolution of neural plasticity in digital organisms LeighSheneman.html
135. 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
136. 1 Sipper2019tinyGP Tiny Genetic Programming in Python MosheSipper.html
137. 1 conf/ibica/SlapakN14 Multiobjective Genetic Programming of Agent Decision Strategies MartinSlapak.html RomanNeruda.html
138. 2 Spector:2024:GPEM Chief editorship transition LeeSpector.html LeonardoTrujillo.html
139. 2 Swan:2014:SMGP Semantically-meaningful Numeric Constants for Genetic Programming JerrySwan.html JohnHDrake.html KrzysztofKrawiec.html
140. 2 swan:2014:SMGP2 Analysis of Semantic Building Blocks via Groebner Bases JerrySwan.html GeoffreyKNeumann.html KrzysztofKrawiec.html
141. 26 Tackett93 Genetic Generation of ``Dendritic'' Trees for Image Classification WalterAldenTackett.html
142. 3 Tackett:1994:thesis Recombination, Selection, and the Genetic Construction of Computer Programs WalterAldenTackett.html
143. 1 Uusitalo:2024:GPEM Creative collaboration with interactive evolutionary algorithms: a reflective exploratory design study SeveriUusitalo.html AnnaKantosalo.html AnttiSalovaara.html TapioTakala.html ChristianGuckelsberger.html
144. 1 VanneschiPoliHNC2011 Genetic Programming: Introduction, Applications, Theory and Open Issues LeonardoVanneschi.html RiccardoPoli.html
145. 1 Vanneschi:book Lectures on Intelligent Systems LeonardoVanneschi.html SaraSilva.html
146. 32 DBLP:journals/asc/WanWZCBWZLG24 Label reusing based graph neural network for unbalanced classification of personalized driver genes in cancer Han-WenWan.html Meng-HanWu.html Wen-ShanZhao.html HanCheng.html YingBi.html Xian-FangWang.html Xiang-RuiZhang.html YanLi.html Wei-FengGuo.html
147. 1 wang:2024:CEC Dimensionality Reduction for Classification Using Divide-and-Conquer Based Genetic Programming PengWang2.html BingXue.html JingLiang.html MengjieZhang.html
148. 3 Watkinson:2023:GI Updating Gin's profiler for current Java MylesWatkinson.html AlexanderEIBrownlee.html
149. 1 Wen:2016:CEC Learning Ensemble of Decision Trees through Multifactorial Genetic Programming Yu-WeiWen.html Chuan-KangTing.html
150. 1 Worm:thesis Prioritized Grammar Enumeration: A novel method for symbolic regression TonyWorm.html
151. 10 Xing:2019:IBF Automatic Software Merging using Automated Program Repair XiaoqianXing.html KatsuhisaMaruyama.html
152. 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
153. 1 yakubu:thesis Supporting new product development using customers' online data and computational intelligence methods HananYakubu.html
154. 6 Yunhan_Yang:2021:CEC Genetic Programming for Symbolic Regression: A Study on Fish Weight Prediction YunhanYang.html BingXue.html LinleyJesson.html MengjieZhang.html
155. 5 Zhang:ieeeTEC2 SR-Forest: A Genetic Programming based Heterogeneous Ensemble Learning Method HengzheZhang.html AiminZhou.html QiChen.html BingXue.html MengjieZhang.html
156. 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
157. 20 ZHANG:2022:knosys Evolving ensembles using multi-objective genetic programming for imbalanced classification LiangZhang2.html KefanWang.html LuyuanXu.html WenjiaSheng.html QiKang.html

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