Genetic Programming Bibliography entries for Leonardo Vanneschi

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GP coauthors/coeditors: Francesca Abbona, Marco Bona, Mario Giacobini, Francesco Archetti, Stefano Lanzeni, Enza Messina, Mauro Castelli, Ilaria Giordani, Irene Azzali, Sara Silva, Illya Bakurov, Andrea Mosca, Luigi Bertolotti, Marco Ivaldi, Nicole Dalia Cilia, Claudio De Stefano, Francesco R Fontanella, Maria Joao Freitas, Marco Buzzelli, Raimondo Schettini, Olivier Gau, Alessandra Scotto di Freca, Jose Manuel Munoz Contreras, Nuno Miguel Rodrigues Domingos, Leonardo Trujillo, Palina Bartashevich, Sanaz Mostaghim, Joao E Batista, Ana Isabel Rosa Cabral, Maria Jose Vasconcelos, Joao Eduardo Batista, Christian Blum, Enrique Alba, Thomas Bartz-Beielstein, Daniele Loiacono, Francisco Luna Valero, Jorn Mehnen, Gabriela Ochoa, Mike Preuss, Emilia Tantar, Kent McClymont, Ed Keedwell, Emma Hart, Kevin Sim, Steven M Gustafson, Ekaterina (Katya) Vladislavleva, Anne Auger, Bernd Bischl, Dimo Brockhoff, Nikolaus Hansen, Olaf Mersmann, Petr Posik, Heike Trautmann, Muhammad Iqbal, Kamran Shafi, Ryan J Urbanowicz, Stefan Wagner, Michael Affenzeller, David Walker, Richard Everson, Jonathan E Fieldsend, Forrest Stonedahl, William Michael Rand, Stephen L Smith, Stefano Cagnoni, Robert M Patton, Gisele L Pappa, John R Woodward, Jerry Swan, Krzysztof Krawiec, Alexandru-Adrian Tantar, Peter A N Bosman, Miguel Vega-Rodriguez, Jose M Chaves-Gonzalez, David L Gonzalez-Alvarez, Sergio Santander-Jimenez, Lee Spector, Maarten Keijzer, Kenneth L Holladay, Tea Tusar, Boris Naujoks, Jaume Bacardit, Josh C Bongard, Jurgen Branke, Nicolas Bredeche, Francisco Chicano, Alan Dorin, Rene Doursat, Aniko Ekart, Tobias Friedrich, Mark Harman, Hitoshi Iba, Christian Igel, Thomas Jansen, Tim Kovacs, Taras Kowaliw, Manuel Lopez-Ibanez, Jose A Lozano, Gabriel Luque, John A W McCall, Alberto Moraglio, Alison A Motsinger, Frank Neumann, Gustavo Olague, Yew-Soon Ong, Michael E Palmer, Konstantinos E Parsopoulos, Thomas Schmickl, Christine Solnon, Thomas Stuetzle, El-Ghazali Talbi, Daniel R Tauritz, Martin Pelikan, Dirk V Arnold, Anthony Brabazon, Martin V Butz, Jeff Clune, Myra B Cohen, Kalyanmoy Deb, Andries P Engelbrecht, Natalio Krasnogor, Julian F Miller, Michael O'Neill, Kumara Sastry, Dirk Thierens, Jano I van Hemert, Carsten Witt, Karina Brotto Rebuli, Niccolo Tallone, Pedro C Silva, Luca Manzoni, Luis Catarino, Joao Manuel de Brito Carreiras, Davide Castaldi, Daniele Maccagnola, Stefano Ruberto, Roberto Henriques, Matteo De Felice, Ales Popovic, Emigdio Z-Flores, Pierrick Legrand, Ivo Goncalves, Manuel Clergue, Philippe Collard, Marco Tomassini, Marc Ebner, Anna Esparcia-Alcazar, Antonella Farinaccio, Giancarlo Mauri, Paolo Provero, Davide Farinati, Francisco Fernandez de Vega, Laurent Bucher, Giandomenico Spezzano, Philipp Fleck, Stephan M Winkler, Michael Kommenda, Gianluigi Folino, Clara Pizzuti, German Galeano, Carlos Antonio Goribar Jimenez, Yazmin Maldonado Robles, Petr Hajek, Vijay Ingalalli, William La Cava, Jason H Moore, Kourosh Danai, Uriel Lopez, Francesco Marchetti, James McDermott, Una-May O'Reilly, Kalyan Veeramachaneni, David Robert White, Sean Luke, Wojciech Jaskowski, Robin Harper, Kenneth De Jong, Gabriel Kronberger, Patryk Orzechowski, Roman Tobias Kalkreuth, Luis Munoz Delgado, Giorgia Nadizar, Fraser Garrow, Berfin Sakallioglu, Lorenzo Canonne, Ivanoe De Falco, Antonio Della Cioppa, Ernesto Tarantino, Wolfgang Banzhaf, Daniele M Papetti, Andrea Tangherloni, Paolo Cazzaniga, Riccardo Poli, Nicholas Freitag McPhee, William B Langdon, Alessandro Re, Denis Rochat, Liah Rosenfeld, Stephen Dignum, Susana de Almeida Mendes Vinga Martins, Joana B Melo, Jose Miguel Ranhada Vellez Caldas, Jerome Cuendet, Perla Sarahi Juarez-Smith, Oliver Schuetze, Sebastien Verel, Andrea Valsecchi, Yuri Pirola, Giuseppe Cuccu, Marco Antoniotti, Luca Mussi, Mauro Antoniotti, Matteo Mondini, Martino Bertoni, Alberto Ronchi, Mattia Stefano, Ernesto Costa, Henrique Vaz, Victor Jose de Almeida e Sousa Lobo, Paulo Urbano, Bernardo Galvao, Kristen M Scott, David Micha Horn, Giacomo Zoppi,

Genetic Programming Articles by Leonardo Vanneschi

1. Giorgia Nadizar and Berfin Sakallioglu and Fraser Garrow and Sara Silva and Leonardo Vanneschi. Geometric semantic GP with linear scaling: Darwinian versus Lamarckian evolution. Genetic Programming and Evolvable Machines, 25:Article no: 17, 2024. Online first. details

2. Davide Farinati and Leonardo Vanneschi. A survey on dynamic populations in bio-inspired algorithms. Genetic Programming and Evolvable Machines, 25:Article no 19, 2024. Online first. details

3. Illya Bakurov and Jose Manuel Munoz Contreras and Mauro Castelli and Nuno Rodrigues and Sara Silva and Leonardo Trujillo and Leonardo Vanneschi. Geometric semantic genetic programming with normalized and standardized random programs. Genetic Programming and Evolvable Machines, 25:Article no 6, 2024. Online first. details

4. Irene Azzali and Nicole D. Cilia and Claudio De Stefano and Francesco Fontanella and Mario Giacobini and Leonardo Vanneschi. Automatic feature extraction with Vectorial Genetic Programming for Alzheimer's Disease prediction through handwriting analysis. Swarm and Evolutionary Computation, 87:101571, 2024. details

5. Nuno M. Rodrigues and Joao E. Batista and William La Cava and Leonardo Vanneschi and Sara Silva. Exploring SLUG: Feature Selection Using Genetic Algorithms and Genetic Programming. SN Computer Science, 5(1) 2023. details

6. Leonardo Vanneschi and Leonardo Trujillo. Introduction to the peer commentary special section on ``Jaws 30'' by W. B. Langdon. Genetic Programming and Evolvable Machines, 24(2):Article number: 18, 2023. Special Issue: Thirtieth Anniversary of Genetic Programming: On the Programming of Computers by Means of Natural Selection \citekoza:book. details

7. Daniele M. Papetti and Andrea Tangherloni and Davide Farinati and Paolo Cazzaniga and Leonardo Vanneschi. Simplifying Fitness Landscapes Using Dilation Functions Evolved With Genetic Programming. IEEE Computational Intelligence Magazine, 18(1):22-31, 2023. details

8. Davide Farinati and Illya Bakurov and Leonardo Vanneschi. A study of dynamic populations in geometric semantic genetic programming. Information Sciences, 648:119513, 2023. details

9. Illya Bakurov and Marco Buzzelli and Raimondo Schettini and Mauro Castelli and Leonardo Vanneschi. Full-Reference Image Quality Expression via Genetic Programming. IEEE Trans. Image Process., 32:1458-1473, 2023. details

10. Illya Bakurov and Marco Buzzelli and Raimondo Schettini and Mauro Castelli and Leonardo Vanneschi. Semantic segmentation network stacking with genetic programming. Genetic Programming and Evolvable Machines, 24(2):Article number: 15, 2023. Special Issue on Highlights of Genetic Programming 2022 EventsOnline first. details

11. Francesca Abbona and Leonardo Vanneschi and Mario Giacobini. Towards a Vectorial Approach to Predict Beef Farm Performance. Applied Sciences, 12(3) 2022. details

12. James McDermott and Gabriel Kronberger and Patryk Orzechowski and Leonardo Vanneschi and Luca Manzoni and Roman Kalkreuth and Mauro Castelli. Genetic Programming Benchmarks: Looking Back and Looking Forward. SIGEVOlution newsletter of the ACM Special Interest Group on Genetic and Evolutionary Computation, 15(3) 2022. details

13. I. Bakurov and M. Castelli and F. Fontanella and A. Scotto di Freca and L. Vanneschi. A novel binary classification approach based on geometric semantic genetic programming. Swarm and Evolutionary Computation, 69:101028, 2022. details

14. Joao E. Batista and Ana I. R. Cabral and Maria J. P. Vasconcelos and Leonardo Vanneschi and Sara Silva. Improving Land Cover Classification Using Genetic Programming for Feature Construction. Remote Sensing, 13(9) 2021. details

15. Leonardo Vanneschi and Mauro Castelli. Soft target and functional complexity reduction: A hybrid regularization method for genetic programming. Expert Systems with Applications, 177:114929, 2021. details

16. Illya Bakurov and Marco Buzzelli and Mauro Castelli and Leonardo Vanneschi and Raimondo Schettini. General Purpose Optimization Library (GPOL): A Flexible and Efficient Multi-Purpose Optimization Library in Python. Applied Sciences, 11(11):Article-number 4774, 2021. details

17. Illya Bakurov and Mauro Castelli and Olivier Gau and Francesco Fontanella and Leonardo Vanneschi. Genetic programming for stacked generalization. Swarm and Evolutionary Computation, 65:100913, 2021. details

18. Nuno M. Rodrigues and Sara Silva and Leonardo Vanneschi. A Study of Generalization and Fitness Landscapes for Neuroevolution. IEEE Access, 8:108216-108234, 2020. details

19. Irene Azzali and Leonardo Vanneschi and Andrea Mosca and Luigi Bertolotti and Mario Giacobini. Towards the use of genetic programming in the ecological modelling of mosquito population dynamics. Genetic Programming and Evolvable Machines, 21(4):629-642, 2020. details

20. Irene Azzali and Leonardo Vanneschi and Illya Bakurov and Sara Silva and Marco Ivaldi and Mario Giacobini. Towards the use of vector based GP to predict physiological time series. Applied Soft Computing, 89:106097, 2020. details

21. Francesca Abbona and Leonardo Vanneschi and Marco Bona and Mario Giacobini. Towards modelling beef cattle management with Genetic Programming. Livestock Science, 241:104205, 2020. details

22. Leonardo Vanneschi and Mauro Castelli and Kristen Scott and Leonardo Trujillo. Alignment-based genetic programming for real life applications. Swarm and Evolutionary Computation, 44:840-851, 2019. details

23. Stefano Ruberto and Leonardo Vanneschi and Mauro Castelli. Genetic programming with semantic equivalence classes. Swarm and Evolutionary Computation, 44:453-469, 2019. details

24. Luis Munoz and Leonardo Trujillo and Sara Silva and Mauro Castelli and Leonardo Vanneschi. Evolving multidimensional transformations for symbolic regression with M3GP. Memetic Computing, 11(2):111-126, 2019. details

25. William La Cava and Sara Silva and Kourosh Danai and Lee Spector and Leonardo Vanneschi and Jason H. Moore. Multidimensional genetic programming for multiclass classification. Swarm and Evolutionary Computation, 44:260-272, 2019. details

26. Leonardo Vanneschi and Mauro Castelli and Kristen Scott and Ales Popovic. Accurate High Performance Concrete Prediction with an Alignment-Based Genetic Programming System. International Journal of Concrete Structures and Materials, 12(1) 2018. details

27. Leonardo Vanneschi and David Micha Horn and Mauro Castelli and Ales Popovic. An artificial intelligence system for predicting customer default in e-commerce. Expert Systems with Applications, 104:1-21, 2018. details

28. Sara Silva and Leonardo Vanneschi and Ana I. R. Cabral and Maria J. Vasconcelos. A semi-supervised Genetic Programming method for dealing with noisy labels and hidden overfitting. Swarm and Evolutionary Computation, 39:323-338, 2018. details

29. Petr Hajek and Roberto Henriques and Mauro Castelli and Leonardo Vanneschi. Forecasting performance of regional innovation systems using semantic-based genetic programming with local search optimizer. Computer \& Operations Research, 2018. details

30. Ana I. R. Cabral and Sara Silva and Pedro C. Silva and Leonardo Vanneschi and Maria J. Vasconcelos. Burned area estimations derived from Landsat ETM+ and OLI data: Comparing Genetic Programming with Maximum Likelihood and Classification and Regression Trees. ISPRS Journal of Photogrammetry and Remote Sensing, 142:94-105, 2018. details

31. Mauro Castelli and Leonardo Vanneschi and Leonardo Trujillo and Ales Popovic. Stock index return forecasting: semantics-based genetic programming with local search optimiser. International Journal of Bio-Inspired Computation, 10(3):159-171, 2017. details

32. Mauro Castelli and Luca Manzoni and Sara Silva and Leonardo Vanneschi and Ales Popovic. The influence of population size in geometric semantic GP. Swarm and Evolutionary Computation, 32:110-120, 2017. details

33. Mauro Castelli and Luca Manzoni and Leonardo Vanneschi and Ales Popovic. An expert system for extracting knowledge from customers' reviews: The case of Amazon.com, Inc.. Expert Systems with Applications, 84:117-126, 2017. details

34. Mauro Castelli and Leonardo Vanneschi and Luca Manzoni and Ales Popovic. Semantic genetic programming for fast and accurate data knowledge discovery. Swarm and Evolutionary Computation, 26 2016. details

35. Mauro Castelli and Leonardo Vanneschi and Ales Popovic. Parameter evaluation of geometric semantic genetic programming in pharmacokinetics. Int. J. of Bio-Inspired Computation, 8(1):42-50, 2016. details

36. Mauro Castelli and Luca Manzoni and Leonardo Vanneschi and Sara Silva and Ales Popovic. Self-tuning geometric semantic Genetic Programming. Genetic Programming and Evolvable Machines, 17(1):55-74, 2016. details

37. Mauro Castelli and Leonardo Vanneschi and Ales Popovic. Controlling Individuals Growth in Semantic Genetic Programming through Elitist Replacement. Computational Intelligence and Neuroscience, 2016. details

38. Mauro Castelli and Leonardo Trujillo and Leonardo Vanneschi and Ales Popovic. Prediction of relative position of CT slices using a computational intelligence system. Applied Soft Computing, 46:537-542, 2016. details

39. Mauro Castelli and Roberto Henriques and Leonardo Vanneschi. A geometric semantic genetic programming system for the electoral redistricting problem. Neurocomputing, 154:200-207, 2015. details

40. Mauro Castelli and Leonardo Vanneschi and Ales Popovic. Predicting Burned Areas of Forest Fires: an Artificial Intelligence Approach. Fire Ecology, 11(1):106-118, 2015. details

41. Mauro Castelli and Leonardo Vanneschi and Matteo De Felice. Forecasting short-term electricity consumption using a semantics-based genetic programming framework: The South Italy case. Energy Economics, 47:37-41, 2015. details

42. Mauro Castelli and Leonardo Trujillo and Leonardo Vanneschi and Ales Popovic. Prediction of energy performance of residential buildings: a genetic programming approach. Energy and Buildings, 102(1):67-74, 2015. details

43. Mauro Castelli and Leonardo Vanneschi and Leonardo Trujillo. Energy Consumption Forecasting using Semantics Based Genetic Programming with Local Search Optimizer. Computational Intelligence and Neuroscience, 2015 2015. details

44. Mauro Castelli and Sara Silva and Leonardo Vanneschi. A C++ framework for geometric semantic genetic programming. Genetic Programming and Evolvable Machines, 16(1):73-81, 2015. details

45. Leonardo Vanneschi. Improving genetic programming for the prediction of pharmacokinetic parameters. Memetic Computing, 6(4):255-262, 2014. details

46. Leonardo Vanneschi and Mauro Castelli and Sara Silva. A survey of semantic methods in genetic programming. Genetic Programming and Evolvable Machines, 15(2):195-214, 2014. details

47. Mauro Castelli and Leonardo Vanneschi and Sara Silva. Semantic Search-Based Genetic Programming and the Effect of Intron Deletion. IEEE Transactions on Cybernetics, 44(1):103-113, 2014. details

48. Mauro Castelli and Leonardo Vanneschi and Sara Silva. Prediction of the Unified Parkinson's Disease Rating Scale assessment using a genetic programming system with geometric semantic genetic operators. Expert Systems with Applications, 41(10):4608-4616, 2014. details

49. M. Castelli and L. Vanneschi and S. Silva. Corrections to ``Semantic Search Based Genetic Programming and the Effect of Introns Deletion'' [Jan 14 103-113]. IEEE Transactions on Cybernetics, 44(4):565, 2014. details

50. Mauro Castelli and Leonardo Vanneschi and Sara Silva. Semantic Search-Based Genetic Programming and the Effect of Intron Deletion. IEEE Transactions on Cybernetics, 44(1):103-113, 2014. details

51. Leonardo Vanneschi and Matteo Mondini and Martino Bertoni and Alberto Ronchi and Mattia Stefano. Gene regulatory networks reconstruction from time series datasets using genetic programming: a comparison between tree-based and graph-based approaches. Genetic Programming and Evolvable Machines, 14(4):431-455, 2013. details

52. Luca Manzoni and Mauro Castelli and Leonardo Vanneschi. A new genetic programming framework based on reaction systems. Genetic Programming and Evolvable Machines, 14(4):457-471, 2013. details

53. Mauro Castelli and Leonardo Vanneschi and Sara Silva. Prediction of high performance concrete strength using Genetic Programming with geometric semantic genetic operators. Expert Systems with Applications, 40(17):6856-6862, 2013. details

54. Leonardo Vanneschi and Yuri Pirola and Giancarlo Mauri and Marco Tomassini and Philippe Collard and Sebastien Verel. A study of the neutrality of Boolean function landscapes in genetic programming. Theoretical Computer Science, 425:34-57, 2012. details

55. Sara Silva and Stephen Dignum and Leonardo Vanneschi. Operator equalisation for bloat free genetic programming and a survey of bloat control methods. Genetic Programming and Evolvable Machines, 13(2):197-238, 2012. details

56. Sara Silva and Leonardo Vanneschi. Bloat free genetic programming: application to human oral bioavailability prediction. International Journal of Data Mining and Bioinformatics, 6(6):585-601, 2012. details

57. Leonardo Vanneschi and Antonella Farinaccio and Giancarlo Mauri and Mauro Antoniotti and Paolo Provero and Mario Giacobini. A comparison of machine learning techniques for survival prediction in breast cancer. BioData Mining, 4(12) 2011. details

58. Leonardo Vanneschi and Luca Mussi and Stefano Cagnoni. Hot topics in Evolutionary Computation. Intelligenza Artificiale, 5(1):5-17, 2011. details

59. Riccardo Poli and Leonardo Vanneschi and William B. Langdon and Nicholas Freitag McPhee. Theoretical Results in Genetic Programming: The next ten years?. Genetic Programming and Evolvable Machines, 11(3/4):285-320, 2010. Tenth Anniversary Issue: Progress in Genetic Programming and Evolvable Machines. details

60. Marco Tomassini and Leonardo Vanneschi. Guest editorial: special issue on parallel and distributed evolutionary algorithms, part two. Genetic Programming and Evolvable Machines, 11(2):129-130, 2010. Editorial special issue on parallel and distributed evolutionary algorithms, part two. details

61. Michael O'Neill and Leonardo Vanneschi and Steven Gustafson and Wolfgang Banzhaf. Open issues in genetic programming. Genetic Programming and Evolvable Machines, 11(3/4):339-363, 2010. Tenth Anniversary Issue: Progress in Genetic Programming and Evolvable Machines. details

62. Francesco Archetti and Ilaria Giordani and Leonardo Vanneschi. Genetic programming for QSAR investigation of docking energy. Applied Soft Computing, 10(1):170-182, 2010. details

63. Francesco Archetti and Ilaria Giordani and Leonardo Vanneschi. Genetic programming for anticancer therapeutic response prediction using the NCI-60 dataset. Computers \& Operations Research, 37(8):1395-1405, 2010. Operations Research and Data Mining in Biological Systems. details

64. Leonardo Vanneschi and Francesco Archetti and Mauro Castelli and Ilaria Giordani. Classification of Oncologic Data with Genetic Programming. Journal of Artificial Evolution and Applications, 2009 2009. details

65. Steven Gustafson and Leonardo Vanneschi. Crossover-Based Tree Distance in Genetic Programming. IEEE Transactions on Evolutionary Computation, 12(4):506-524, 2008. details

66. Francesco Archetti and Stefano Lanzeni and Enza Messina and Leonardo Vanneschi. Genetic programming for computational pharmacokinetics in drug discovery and development. Genetic Programming and Evolvable Machines, 8(4):413-432, 2007. special issue on medical applications of Genetic and Evolutionary Computation. details

67. Marco Tomassini and Leonardo Vanneschi and Philippe Collard and Manuel Clergue. A Study of Fitness Distance Correlation as a Difficulty Measure in Genetic Programming. Evolutionary Computation, 13(2):213-239, 2005. details

68. Francisco Fernandez and Marco Tomassini and Leonardo Vanneschi. An Empirical Study of Multipopulation Genetic Programming. Genetic Programming and Evolvable Machines, 4(1):21-51, 2003. details

Genetic Programming Books by Leonardo Vanneschi

• Leonardo Vanneschi and Sara Silva. Lectures on Intelligent Systems. Springer, 2023. details

Genetic Programming PhD doctoral thesis Leonardo Vanneschi

• Leonardo Vanneschi. Theory and Practice for Efficient Genetic Programming. PhD thesis, Faculty of Sciences, University of Lausanne, Switzerland, 2004. details

Genetic Programming Conference proceedings edited by Leonardo Vanneschi

1. Christian Blum and Enrique Alba and Thomas Bartz-Beielstein and Daniele Loiacono and Francisco Luna and Joern Mehnen and Gabriela Ochoa and Mike Preuss and Emilia Tantar and Leonardo Vanneschi and Kent McClymont and Ed Keedwell and Emma Hart and Kevin Sim and Steven Gustafson and Ekaterina Vladislavleva and Anne Auger and Bernd Bischl and Dimo Brockhoff and Nikolaus Hansen and Olaf Mersmann and Petr Posik and Heike Trautmann and Muhammad Iqbal and Kamran Shafi and Ryan Urbanowicz and Stefan Wagner and Michael Affenzeller and David Walker and Richard Everson and Jonathan Fieldsend and Forrest Stonedahl and William Rand and Stephen L. Smith and Stefano Cagnoni and Robert M. Patton and Gisele L. Pappa and John Woodward and Jerry Swan and Krzysztof Krawiec and Alexandru-Adrian Tantar and Peter A. N. Bosman and Miguel Vega-Rodriguez and Jose M. Chaves-Gonzalez and David L. Gonzalez-Alvarez and Sergio Santander-Jimenez and Lee Spector and Maarten Keijzer and Kenneth Holladay and Tea Tusar and Boris Naujoks editors, GECCO '13 Companion: Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation conference companion. Amsterdam, The Netherlands, 2013. details

2. Christian Blum and Enrique Alba and Anne Auger and Jaume Bacardit and Josh Bongard and Juergen Branke and Nicolas Bredeche and Dimo Brockhoff and Francisco Chicano and Alan Dorin and Rene Doursat and Aniko Ekart and Tobias Friedrich and Mario Giacobini and Mark Harman and Hitoshi Iba and Christian Igel and Thomas Jansen and Tim Kovacs and Taras Kowaliw and Manuel Lopez-Ibanez and Jose A. Lozano and Gabriel Luque and John McCall and Alberto Moraglio and Alison Motsinger-Reif and Frank Neumann and Gabriela Ochoa and Gustavo Olague and Yew-Soon Ong and Michael E. Palmer and Gisele Lobo Pappa and Konstantinos E. Parsopoulos and Thomas Schmickl and Stephen L. Smith and Christine Solnon and Thomas Stuetzle and El-Ghazali Talbi and Daniel Tauritz and Leonardo Vanneschi editors, GECCO '13: Proceeding of the fifteenth annual conference on Genetic and evolutionary computation conference. Amsterdam, The Netherlands, 2013. details

3. Juergen Branke and Martin Pelikan and Enrique Alba and Dirk V. Arnold and Josh Bongard and Anthony Brabazon and Juergen Branke and Martin V. Butz and Jeff Clune and Myra Cohen and Kalyanmoy Deb and Andries P Engelbrecht and Natalio Krasnogor and Julian F. Miller and Michael O'Neill and Kumara Sastry and Dirk Thierens and Jano van Hemert and Leonardo Vanneschi and Carsten Witt editors, GECCO '10: Proceedings of the 12th annual conference on Genetic and evolutionary computation. Portland, OR, USA, ACM, 2010. details

4. Leonardo Vanneschi and Steven Gustafson and Alberto Moraglio and Ivanoe De Falco and Marc Ebner editors, Proceedings of the 12th European Conference on Genetic Programming, EuroGP 2009. Volume 5481 of LNCS, Tuebingen, Springer, 2009. details

5. Michael O'Neill and Leonardo Vanneschi and Steven Gustafson and Anna Isabel Esparcia Alcazar and Ivanoe De Falco and Antonio Della Cioppa and Ernesto Tarantino editors, Proceedings of the 11th European Conference on Genetic Programming, EuroGP 2008. Volume 4971 of Lecture Notes in Computer Science, Naples, Springer, 2008. details

6. Marc Ebner and Michael O'Neill and Anik\'o Ek\'art and Leonardo Vanneschi and Anna Isabel Esparcia-Alc\'azar editors, Proceedings of the 10th European Conference on Genetic Programming. Volume 4445 of Lecture Notes in Computer Science, Valencia, Spain, Springer, 2007. details

Genetic Programming conference papers by Leonardo Vanneschi

1. Francesco Marchetti and Mauro Castelli and Illya Bakurov and Leonardo Vanneschi. Full Inclusive Genetic Programming. In Bing Xue editor, 2024 IEEE Congress on Evolutionary Computation (CEC), Yokohama, Japan, 2024. IEEE. details

2. Joao Eduardo Batista and Nuno Miguel Rodrigues and Leonardo Vanneschi and Sara Silva. M6GP: Multiobjective Feature Engineering. In Bing Xue editor, 2024 IEEE Congress on Evolutionary Computation (CEC), Yokohama, Japan, 2024. IEEE. details

3. Leonardo Vanneschi. Exploring Non-Bloating Geometric Semantic Genetic Programming. In Wolfgang Banzhaf and Ting Hu and Alexander Lalejini and Stephan Winkler editors, Genetic Programming Theory and Practice XXI, University of Michigan, USA, 2024. details

4. Leonardo Vanneschi. SLIM-GSGP: The Non-bloating Geometric Semantic Genetic Programming. In Mario Giacobini and Bing Xue and Luca Manzoni editors, EuroGP 2024: Proceedings of the 27th European Conference on Genetic Programming, volume 14631, pages 125-141, Aberystwyth, 2024. Springer. details

5. Davide Farinati and Leonardo Vanneschi. GM4OS: An Evolutionary Oversampling Approach for Imbalanced Binary Classification Tasks. In Stephen Smith and Joao Correia and Christian Cintrano editors, 27th International Conference, EvoApplications 2024, volume 14634, pages 68-82, Aberystwyth, 2024. Springer. details

6. Giorgia Nadizar and Fraser Garrow and Berfin Sakallioglu and Lorenzo Canonne and Sara Silva and Leonardo Vanneschi. An Investigation of Geometric Semantic GP with Linear Scaling. In Sara Silva and Luis Paquete and Leonardo Vanneschi and Nuno Lourenco and Ales Zamuda and Ahmed Kheiri and Arnaud Liefooghe and Bing Xue and Ying Bi and Nelishia Pillay and Irene Moser and Arthur Guijt and Jessica Catarino and Pablo Garcia-Sanchez and Leonardo Trujillo and Carla Silva and Nadarajen Veerapen editors, Proceedings of the 2023 Genetic and Evolutionary Computation Conference, pages 1165-1174, Lisbon, Portugal, 2023. Association for Computing Machinery. details

7. Philipp Fleck and Stephan Winkler and Michael Kommenda and Sara Silva and Leonardo Vanneschi and Michael Affenzeller. Evolutionary Algorithms for Segment Optimization in Vectorial GP. In Sara Silva and Luis Paquete and Leonardo Vanneschi and Nuno Lourenco and Ales Zamuda and Ahmed Kheiri and Arnaud Liefooghe and Bing Xue and Ying Bi and Nelishia Pillay and Irene Moser and Arthur Guijt and Jessica Catarino and Pablo Garcia-Sanchez and Leonardo Trujillo and Carla Silva and Nadarajen Veerapen editors, Proceedings of the 2023 Genetic and Evolutionary Computation Conference, pages 439-442, Lisbon, Portugal, 2023. Association for Computing Machinery. details

8. Karina Brotto Rebuli and Mario Giacobini and Sara Silva and Leonardo Vanneschi. A Comparison of Structural Complexity Metrics for Explainable Genetic Programming. In Sara Silva and Luis Paquete and Leonardo Vanneschi and Nuno Lourenco and Ales Zamuda and Ahmed Kheiri and Arnaud Liefooghe and Bing Xue and Ying Bi and Nelishia Pillay and Irene Moser and Arthur Guijt and Jessica Catarino and Pablo Garcia-Sanchez and Leonardo Trujillo and Carla Silva and Nadarajen Veerapen editors, Proceedings of the 2023 Genetic and Evolutionary Computation Conference, pages 539-542, Lisbon, Portugal, 2023. Association for Computing Machinery. details

9. Karina Brotto Rebuli and Mario Giacobini and Niccolo Tallone and Leonardo Vanneschi. A preliminary study of Prediction Interval Methods with Genetic Programming. In Heike Trautmann and Carola Doerr and Alberto Moraglio and Thomas Bartz-Beielstein and Bogdan Filipic and Marcus Gallagher and Yew-Soon Ong and Abhishek Gupta and Anna V Kononova and Hao Wang and Michael Emmerich and Peter A. N. Bosman and Daniela Zaharie and Fabio Caraffini and Johann Dreo and Anne Auger and Konstantin Dietric and Paul Dufosse and Tobias Glasmachers and Nikolaus Hansen and Olaf Mersmann and Petr Posik and Tea Tusar and Dimo Brockhoff and Tome Eftimov and Pascal Kerschke and Boris Naujoks and Mike Preuss and Vanessa Volz and Bilel Derbel and Ke Li and Xiaodong Li and Saul Zapotecas and Qingfu Zhang and Mark Coletti and Catherine (Katie) Schuman and Eric ``Siggy'' Scott and Robert Patton and Paul Wiegand and Jeffrey K. Bassett and Chathika Gunaratne and Tinkle Chugh and Richard Allmendinger and Jussi Hakanen and Daniel Tauritz and John Woodward and Manuel Lopez-Ibanez and John McCall and Jaume Bacardit and Alexander Brownlee and Stefano Cagnoni and Giovanni Iacca and David Walker and Jamal Toutouh and UnaMay O'Reilly and Penousal Machado and Joao Correia and Sergio Nesmachnow and Josu Ceberio and Rafael Villanueva and Ignacio Hidalgo and Francisco Fernandez de Vega and Giuseppe Paolo and Alex Coninx and Antoine Cully and Adam Gaier and Stefan Wagner and Michael Affenzeller and Bobby R. Bruce and Vesna Nowack and Aymeric Blot and Emily Winter and William B. Langdon and Justyna Petke and Silvino Fernandez Alzueta and Pablo Valledor Pellicer and Thomas Stuetzle and David Paetzel and Alexander Wagner and Michael Heider and Nadarajen Veerapen and Katherine Malan and Arnaud Liefooghe and Sebastien Verel and Gabriela Ochoa and Mohammad Nabi Omidvar and Yuan Sun and Ernesto Tarantino and De Falco Ivanoe and Antonio Della Cioppa and Scafuri Umberto and John Rieffel and Jean-Baptiste Mouret and Stephane Doncieux and Stefanos Nikolaidis and Julian Togelius and Matthew C. Fontaine and Serban Georgescu and Francisco Chicano and Darrell Whitley and Oleksandr Kyriienko and Denny Dahl and Ofer Shir and Lee Spector and Alma Rahat and Richard Everson and Jonathan Fieldsend and Handing Wang and Yaochu Jin and Erik Hemberg and Marwa A. Elsayed and Michael Kommenda and William La Cava and Gabriel Kronberger and Steven Gustafson editors, Proceedings of the 2022 Genetic and Evolutionary Computation Conference Companion, pages 530-533, Boston, USA, 2022. Association for Computing Machinery. details

10. Illya Bakurov and Marco Buzzelli and Mauro Castelli and Raimondo Schettini and Leonardo Vanneschi. Genetic Programming for Structural Similarity Design at Multiple Spatial Scales. In Alma Rahat and Jonathan Fieldsend and Markus Wagner and Sara Tari and Nelishia Pillay and Irene Moser and Aldeida Aleti and Ales Zamuda and Ahmed Kheiri and Erik Hemberg and Christopher Cleghorn and Chao-li Sun and Georgios Yannakakis and Nicolas Bredeche and Gabriela Ochoa and Bilel Derbel and Gisele L. Pappa and Sebastian Risi and Laetitia Jourdan and Hiroyuki Sato and Petr Posik and Ofer Shir and Renato Tinos and John Woodward and Malcolm Heywood and Elizabeth Wanner and Leonardo Trujillo and Domagoj Jakobovic and Risto Miikkulainen and Bing Xue and Aneta Neumann and Richard Allmendinger and Inmaculada Medina-Bulo and Slim Bechikh and Andrew M. Sutton and Pietro Simone Oliveto editors, Proceedings of the 2022 Genetic and Evolutionary Computation Conference, pages 911-919, Boston, USA, 2022. Association for Computing Machinery. details

11. Giacomo Zoppi and Leonardo Vanneschi and Mario Giacobini. Reducing the Number of Training Cases in Genetic Programming. In Carlos A. Coello Coello and Sanaz Mostaghim editors, 2022 IEEE Congress on Evolutionary Computation (CEC), Padua, Italy, 2022. details

12. Liah Rosenfeld and Leonardo Vanneschi. EGSGP: an Ensemble System Based on Geometric Semantic GeneticProgramming. In Claudio De Stefano and Francesco Fontanella and Leonardo Vanneschi editors, WIVACE 2022, XVI International Workshop on Artificial Life and Evolutionary Computation, volume 1780, pages 278-290, Gaeta (LT), Italy, 2022. Springer. details

13. Nuno Rodrigues and Joao Batista and William La Cava and Leonardo Vanneschi and Sara Silva. SLUG: Feature Selection Using Genetic Algorithms and Genetic Programming. In Eric Medvet and Gisele Pappa and Bing Xue editors, EuroGP 2022: Proceedings of the 25th European Conference on Genetic Programming, volume 13223, pages 68-84, Madrid, Spain, 2022. Springer Verlag. details

14. Karina Brotto Rebuli and Mario Giacobini and Niccolo Tallone and Leonardo Vanneschi. Single and Multi-objective Genetic Programming Methods for Prediction Intervals. In Claudio De Stefano and Francesco Fontanella and Leonardo Vanneschi editors, WIVACE 2022, XVI International Workshop on Artificial Life and Evolutionary Computation, volume 1780, pages 205-218, Gaeta (LT), Italy, 2022. Springer. details

15. Irene Azzali and Nicole Dalia Cilia and Claudio De Stefano and Francesco Fontanella and Mario Giacobini and Leonardo Vanneschi. Vectorial GP for Alzheimer's Disease Prediction Through Handwriting Analysis. In Juan Luis Jimenez Laredo and J. Ignacio Hidalgo and Kehinde Oluwatoyin Babaagba editors, 25th International Conference, EvoApplications 2022, volume 13224, pages 517-530, Madrid, 2022. Springer. details

16. Karina Brotto Rebuli and Leonardo Vanneschi. Progressive Insular Cooperative GP. In Ting Hu and Nuno Lourenco and Eric Medvet editors, EuroGP 2021: Proceedings of the 24th European Conference on Genetic Programming, volume 12691, pages 19-35, Virtual Event, 2021. Springer Verlag. details

17. Leonardo Vanneschi and Mauro Castelli and Luca Manzoni and Sara Silva and Leonardo Trujillo. Is k Nearest Neighbours Regression Better than GP?. In Ting Hu and Nuno Lourenco and Eric Medvet editors, EuroGP 2020: Proceedings of the 23rd European Conference on Genetic Programming, volume 12101, pages 244-261, Seville, Spain, 2020. Springer Verlag. details

18. Nuno M. Rodrigues and Sara Silva and Leonardo Vanneschi. A Study of Fitness Landscapes for Neuroevolution. In Yaochu Jin editor, 2020 IEEE Congress on Evolutionary Computation (CEC), 2020. details

19. Uriel Lopez and Leonardo Trujillo and Sara Silva and Leonardo Vanneschi and Pierrick Legrand. Unlabeled Multi-Target Regression with Genetic Programming. In Carlos Artemio Coello Coello and Arturo Hernandez Aguirre and Josu Ceberio Uribe and Mario Garza Fabre and Gregorio Toscano Pulido and Katya Rodriguez-Vazquez and Elizabeth Wanner and Nadarajen Veerapen and Efren Mezura Montes and Richard Allmendinger and Hugo Terashima Marin and Markus Wagner and Thomas Bartz-Beielstein and Bogdan Filipic and Heike Trautmann and Ke Tang and John Koza and Erik Goodman and William B. Langdon and Miguel Nicolau and Christine Zarges and Vanessa Volz and Tea Tusar and Boris Naujoks and Peter A. N. Bosman and Darrell Whitley and Christine Solnon and Marde Helbig and Stephane Doncieux and Dennis G. Wilson and Francisco Fernandez de Vega and Luis Paquete and Francisco Chicano and Bing Xue and Jaume Bacardit and Sanaz Mostaghim and Jonathan Fieldsend and Oliver Schuetze and Dirk Arnold and Gabriela Ochoa and Carlos Segura and Carlos Cotta and Michael Emmerich and Mengjie Zhang and Robin Purshouse and Tapabrata Ray and Justyna Petke and Fuyuki Ishikawa and Johannes Lengler and Frank Neumann editors, Proceedings of the 2020 Genetic and Evolutionary Computation Conference, pages 976-984, internet, 2020. Association for Computing Machinery. details

20. Irene Azzali and Leonardo Vanneschi and Mario Giacobini. Investigating the Use of Geometric Semantic Operators in Vectorial Genetic Programming. In Ting Hu and Nuno Lourenco and Eric Medvet editors, EuroGP 2020: Proceedings of the 23rd European Conference on Genetic Programming, volume 12101, pages 52-67, Seville, Spain, 2020. Springer Verlag. details

21. Francesca Abbona and Leonardo Vanneschi and Marco Bona and Mario Giacobini. A GP Approach for Precision Farming. In Yaochu Jin editor, 2020 IEEE Congress on Evolutionary Computation, CEC 2020, page paper id24248, internet, 2020. IEEE Press. details

22. Alessandro Re and Leonardo Vanneschi and Mauro Castelli. Universal Learning Machine with Genetic Programming. In Juan Julian Merelo Guervos and Jonathan M. Garibaldi and Alejandro Linares-Barranco and Kurosh Madani and Kevin Warwick editors, Proceedings of the 11th International Joint Conference on Computational Intelligence, IJCCI 2019, volume 1, pages 115-122, Vienna, Austria, 2019. ScitePress. details

23. Illya Bakurov and Mauro Castelli and Francesco Fontanella and Leonardo Vanneschi. A Regression-like Classification System for Geometric Semantic Genetic Programming. In Juan Julian Merelo Guervos and Jonathan M. Garibaldi and Alejandro Linares-Barranco and Kurosh Madani and Kevin Warwick editors, Proceedings of the 11th International Joint Conference on Computational Intelligence, IJCCI 2019, Vienna, Austria, September 17-19, 2019, pages 40-48, 2019. ScitePress. details

24. Illya Bakurov and Leonardo Vanneschi and Mauro Castelli and Maria Joao Freitas. Supporting Medical Decisions for Treating Rare Diseases through Genetic Programming. In Paul Kaufmann and Pedro A. Castillo editors, 22nd International Conference, EvoApplications 2019, volume 11454, pages 187-203, Leipzig, Germany, 2019. Springer Verlag. details

25. Irene Azzali and Leonardo Vanneschi and Sara Silva and Illya Bakurov and Mario Giacobini. A Vectorial Approach to Genetic Programming. In Lukas Sekanina and Ting Hu and Nuno Lourenco editors, EuroGP 2019: Proceedings of the 22nd European Conference on Genetic Programming, volume 11451, pages 213-227, Leipzig, Germany, 2019. Springer Verlag. details

26. Leonardo Vanneschi and Kristen Scott and Mauro Castelli. A Multiple Expression Alignment Framework for Genetic Programming. In Mauro Castelli and Lukas Sekanina and Mengjie Zhang and Stefano Cagnoni and Pablo Garcia-Sanchez editors, EuroGP 2018: Proceedings of the 21st European Conference on Genetic Programming, volume 10781, pages 166-183, Parma, Italy, 2018. Springer Verlag. details

27. William La Cava and Sara Silva and Kourosh Danai and Lee Spector and Leonardo Vanneschi and Jason H. Moore. A multidimensional genetic programming approach for identifying epsistatic gene interactions. In Carlos Cotta and Tapabrata Ray and Hisao Ishibuchi and Shigeru Obayashi and Bogdan Filipic and Thomas Bartz-Beielstein and Grant Dick and Masaharu Munetomo and Silvino Fernandez Alzueta and Thomas Stuetzle and Pablo Valledor Pellicer and Manuel Lopez-Ibanez and Daniel R. Tauritz and Pietro S. Oliveto and Thomas Weise and Borys Wrobel and Ales Zamuda and Anne Auger and Julien Bect and Dimo Brockhoff and Nikolaus Hansen and Rodolphe Le Riche and Victor Picheny and Bilel Derbel and Ke Li and Hui Li and Xiaodong Li and Saul Zapotecas and Qingfu Zhang and Stephane Doncieux and Richard Duro and Joshua Auerbach and Harold de Vladar and Antonio J. Fernandez-Leiva and JJ Merelo and Pedro A. Castillo-Valdivieso and David Camacho-Fernandez and Francisco Chavez de la O and Ozgur Akman and Khulood Alyahya and Juergen Branke and Kevin Doherty and Jonathan Fieldsend and Giuseppe Carlo Marano and Nikos D. Lagaros and Koichi Nakayama and Chika Oshima and Stefan Wagner and Michael Affenzeller and Boris Naujoks and Vanessa Volz and Tea Tusar and Pascal Kerschke and Riyad Alshammari and Tokunbo Makanju and Brad Alexander and Saemundur O. Haraldsson and Markus Wagner and John R. Woodward and Shin Yoo and John McCall and Nayat Sanchez-Pi and Luis Marti and Danilo Vasconcellos and Masaya Nakata and Anthony Stein and Nadarajen Veerapen and Arnaud Liefooghe and Sebastien Verel and Gabriela Ochoa and Stephen L. Smith and Stefano Cagnoni and Robert M. Patton and William La Cava and Randal Olson and Patryk Orzechowski and Ryan Urbanowicz and Ivanoe De Falco and Antonio Della Cioppa and Ernesto Tarantino and Umberto Scafuri and P. G. M. Baltus and Giovanni Iacca and Ahmed Hallawa and Anil Yaman and Alma Rahat and Handing Wang and Yaochu Jin and David Walker and Richard Everson and Akira Oyama and Koji Shimoyama and Hemant Kumar and Kazuhisa Chiba and Pramudita Satria Palar editors, GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference Companion, pages 23-24, Kyoto, Japan, 2018. ACM. details

28. Mauro Castelli and Ivo Goncalves and Luca Manzoni and Leonardo Vanneschi. Pruning Techniques for Mixed Ensembles of Genetic Programming Models. In Mauro Castelli and Lukas Sekanina and Mengjie Zhang and Stefano Cagnoni and Pablo Garcia-Sanchez editors, EuroGP 2018: Proceedings of the 21st European Conference on Genetic Programming, volume 10781, pages 52-67, Parma, Italy, 2018. Springer Verlag. details

29. Palina Bartashevich and Illya Bakurov and Sanaz Mostaghim and Leonardo Vanneschi. PSO-based Search Rules for Aerial Swarms Against Unexplored Vector Fields via Genetic Programming. In Anne Auger and Carlos M. Fonseca and Nuno Lourenco and Penousal Machado and Luis Paquete and Darrell Whitley editors, 15th International Conference on Parallel Problem Solving from Nature, volume 11101, pages 41-53, Coimbra, Portugal, 2018. Springer. details

30. Palina Bartashevich and Illya Bakurov and Sanaz Mostaghim and Leonardo Vanneschi. Evolving PSO algorithm design in vector fields using geometric semantic GP. In Carlos Cotta and Tapabrata Ray and Hisao Ishibuchi and Shigeru Obayashi and Bogdan Filipic and Thomas Bartz-Beielstein and Grant Dick and Masaharu Munetomo and Silvino Fernandez Alzueta and Thomas Stuetzle and Pablo Valledor Pellicer and Manuel Lopez-Ibanez and Daniel R. Tauritz and Pietro S. Oliveto and Thomas Weise and Borys Wrobel and Ales Zamuda and Anne Auger and Julien Bect and Dimo Brockhoff and Nikolaus Hansen and Rodolphe Le Riche and Victor Picheny and Bilel Derbel and Ke Li and Hui Li and Xiaodong Li and Saul Zapotecas and Qingfu Zhang and Stephane Doncieux and Richard Duro and Joshua Auerbach and Harold de Vladar and Antonio J. Fernandez-Leiva and JJ Merelo and Pedro A. Castillo-Valdivieso and David Camacho-Fernandez and Francisco Chavez de la O and Ozgur Akman and Khulood Alyahya and Juergen Branke and Kevin Doherty and Jonathan Fieldsend and Giuseppe Carlo Marano and Nikos D. Lagaros and Koichi Nakayama and Chika Oshima and Stefan Wagner and Michael Affenzeller and Boris Naujoks and Vanessa Volz and Tea Tusar and Pascal Kerschke and Riyad Alshammari and Tokunbo Makanju and Brad Alexander and Saemundur O. Haraldsson and Markus Wagner and John R. Woodward and Shin Yoo and John McCall and Nayat Sanchez-Pi and Luis Marti and Danilo Vasconcellos and Masaya Nakata and Anthony Stein and Nadarajen Veerapen and Arnaud Liefooghe and Sebastien Verel and Gabriela Ochoa and Stephen L. Smith and Stefano Cagnoni and Robert M. Patton and William La Cava and Randal Olson and Patryk Orzechowski and Ryan Urbanowicz and Ivanoe De Falco and Antonio Della Cioppa and Ernesto Tarantino and Umberto Scafuri and P. G. M. Baltus and Giovanni Iacca and Ahmed Hallawa and Anil Yaman and Alma Rahat and Handing Wang and Yaochu Jin and David Walker and Richard Everson and Akira Oyama and Koji Shimoyama and Hemant Kumar and Kazuhisa Chiba and Pramudita Satria Palar editors, GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference Companion, pages 262-263, Kyoto, Japan, 2018. ACM. details

31. Leonardo Vanneschi and Mauro Castelli and Ivo Goncalves and Luca Manzoni and Sara Silva. Geometric semantic genetic programming for biomedical applications: A state of the art upgrade. In Jose A. Lozano editor, 2017 IEEE Congress on Evolutionary Computation (CEC), pages 177-184, Donostia, San Sebastian, Spain, 2017. IEEE. details

32. Leonardo Vanneschi and Bernardo Galvao. A parallel and distributed semantic Genetic Programming system. In Jose A. Lozano editor, 2017 IEEE Congress on Evolutionary Computation (CEC), pages 121-128, Donostia, San Sebastian, Spain, 2017. IEEE. details

33. Leonardo Vanneschi and Illya Bakurov and Mauro Castelli. An initialization technique for geometric semantic GP based on demes evolution and despeciation. In Jose A. Lozano editor, 2017 IEEE Congress on Evolutionary Computation (CEC), pages 113-120, Donostia, San Sebastian, Spain, 2017. IEEE. details

34. Carlos Goribar-Jimenez and Yazmin Maldonado and Leonardo Trujillo and Mauro Castelli and Ivo Goncalves and Leonardo Vanneschi. Towards the development of a complete GP system on an FPGA using geometric semantic operators. In Jose A. Lozano editor, 2017 IEEE Congress on Evolutionary Computation (CEC), pages 1932-1939, Donostia, San Sebastian, Spain, 2017. IEEE. details

35. Leonardo Vanneschi and Mauro Castelli and Luca Manzoni and Krzysztof Krawiec and Alberto Moraglio and Sara Silva and Ivo Goncalves. PSXO: Population-wide Semantic Crossover. In Proceedings of the Genetic and Evolutionary Computation Conference Companion, pages 257-258, Berlin, Germany, 2017. ACM. details

36. William La Cava and Sara Silva and Leonardo Vanneschi and Lee Spector and Jason Moore. Genetic Programming Representations for Multi-dimensional Feature Learning in Biomedical Classification. In Giovanni Squillero editor, 20th European Conference on the Applications of Evolutionary Computation, volume 10199, pages 158-173, Amsterdam, 2017. Springer. details

37. Mauro Castelli and Luca Manzoni and Ivo Goncalves and Leonardo Vanneschi and Leonardo Trujillo and Sara Silva. An Analysis of Geometric Semantic Crossover: A Computational Geometry Approach. In Proceedings of the 8th International Joint Conference on Computational Intelligence, IJCCI (ECTA) 2016, pages 201-208, 2016. Scitepress. details

38. Leonardo Trujillo and Emigdio Z-Flores and Perla S. Juarez Smith and Pierrick Legrand and Sara Silva and Mauro Castelli and Leonardo Vanneschi and Oliver Schuetze and Luiz Munoz. Local Search is Underused in Genetic Programming. In William Tozier and Brian W. Goldman and Bill Worzel and Rick Riolo editors, Genetic Programming Theory and Practice XIV, pages 119-137, Ann Arbor, USA, 2016. Springer. details

39. Mauro Castelli and Matteo De Felice and Luca Manzoni and Leonardo Vanneschi. Electricity Demand Modelling with Genetic Programming. In Francisco C. Pereira and Penousal Machado and Ernesto Costa and Amilcar Cardoso editors, Progress in Artificial Intelligence - 17th Portuguese Conference on Artificial Intelligence, EPIA 2015, Coimbra, Portugal, September 8-11, 2015. Proceedings, volume 9273, pages 213-225, 2015. Springer. details

40. Leonardo Vanneschi and Mauro Castelli and Ernesto Costa and Alessandro Re and Henrique Vaz and Victor Lobo and Paulo Urbano. Improving Maritime Awareness with Semantic Genetic Programming and Linear Scaling: Prediction of Vessels Position Based on AIS Data. In Antonio M. Mora and Giovanni Squillero editors, 18th European Conference on the Applications of Evolutionary Computation, volume 9028, pages 732-744, Copenhagen, 2015. Springer. details

41. Leonardo Vanneschi. An Introduction to Geometric Semantic Genetic Programming. In Oliver Schuetze and Leonardo Trujillo and Pierrick Legrand and Yazmin Maldonado editors, NEO 2015: Results of the Numerical and Evolutionary Optimization Workshop NEO 2015 held at September 23-25 2015 in Tijuana, Mexico, volume 663, pages 3-42, 2015. Springer. details

42. Sara Silva and Luis Munoz and Leonardo Trujillo and Vijay Ingalalli and Mauro Castelli and Leonardo Vanneschi. Multiclass Classification Through Multidimensinoal Clustering. In Rick Riolo and William P. Worzel and M. Kotanchek and A. Kordon editors, Genetic Programming Theory and Practice XIII, pages 219-239, Ann Arbor, USA, 2015. Springer. details

43. Mauro Castelli and Leonardo Trujillo and Leonardo Vanneschi and Sara Silva and Emigdio Z-Flores and Pierrick Legrand. Geometric Semantic Genetic Programming with Local Search. In Sara Silva and Anna I Esparcia-Alcazar and Manuel Lopez-Ibanez and Sanaz Mostaghim and Jon Timmis and Christine Zarges and Luis Correia and Terence Soule and Mario Giacobini and Ryan Urbanowicz and Youhei Akimoto and Tobias Glasmachers and Francisco Fernandez de Vega and Amy Hoover and Pedro Larranaga and Marta Soto and Carlos Cotta and Francisco B. Pereira and Julia Handl and Jan Koutnik and Antonio Gaspar-Cunha and Heike Trautmann and Jean-Baptiste Mouret and Sebastian Risi and Ernesto Costa and Oliver Schuetze and Krzysztof Krawiec and Alberto Moraglio and Julian F. Miller and Pawel Widera and Stefano Cagnoni and JJ Merelo and Emma Hart and Leonardo Trujillo and Marouane Kessentini and Gabriela Ochoa and Francisco Chicano and Carola Doerr editors, GECCO '15: Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation, pages 999-1006, Madrid, Spain, 2015. ACM. details

44. Stefano Ruberto and Leonardo Vanneschi and Mauro Castelli and Sara Silva. ESAGP -- A Semantic GP Framework Based on Alignment in the Error Space. In Miguel Nicolau and Krzysztof Krawiec and Malcolm I. Heywood and Mauro Castelli and Pablo Garcia-Sanchez and Juan J. Merelo and Victor M. Rivas Santos and Kevin Sim editors, 17th European Conference on Genetic Programming, volume 8599, pages 150-161, Granada, Spain, 2014. Springer. details

45. Vijay Ingalalli and Sara Silva and Mauro Castelli and Leonardo Vanneschi. A Multi-dimensional Genetic Programming Approach for Multi-class Classification Problems. In Miguel Nicolau and Krzysztof Krawiec and Malcolm I. Heywood and Mauro Castelli and Pablo Garcia-Sanchez and Juan J. Merelo and Victor M. Rivas Santos and Kevin Sim editors, 17th European Conference on Genetic Programming, volume 8599, pages 48-60, Granada, Spain, 2014. Springer. details

46. Mauro Castelli and Luca Manzoni and Sara Silva and Leonardo Vanneschi. Self-tuning Geometric Semantic GP. In Colin Johnson and Krzysztof Krawiec and Alberto Moraglio and Michael O'Neill editors, Semantic Methods in Genetic Programming, Ljubljana, Slovenia, 2014. Workshop at Parallel Problem Solving from Nature 2014 conference. details

47. Mauro Castelli and Luca Manzoni and Sara Silva and Leonardo Vanneschi. The Influence of Population Size on Geometric Semantic GP. In Colin Johnson and Krzysztof Krawiec and Alberto Moraglio and Michael O'Neill editors, Semantic Methods in Genetic Programming, Ljubljana, Slovenia, 2014. Workshop at Parallel Problem Solving from Nature 2014 conference. details

48. Mauro Castelli and Leonardo Vanneschi and Sara Silva and Stefano Ruberto. How to Exploit Alignment in the Error Space: Two Different GP Models. In Rick Riolo and William P. Worzel and Mark Kotanchek editors, Genetic Programming Theory and Practice XII, pages 133-148, Ann Arbor, USA, 2014. Springer. details

49. Leonardo Vanneschi and Mauro Castelli and Luca Manzoni and Sara Silva. A New Implementation of Geometric Semantic GP and its Application to Problems in Pharmacokinetics. In Krzysztof Krawiec and Alberto Moraglio and Ting Hu and A. Sima Uyar and Bin Hu editors, Proceedings of the 16th European Conference on Genetic Programming, EuroGP 2013, volume 7831, pages 205-216, Vienna, Austria, 2013. Springer Verlag. details

50. Leonardo Vanneschi. Applications of Genetic Programming in Drug Discovery and Pharmacokinetics. In German Terrazas and Fernando Esteban Barril Otero and Antonio D. Masegosa editors, VI International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO 2013), volume 512, page x, Canterbury, United Kingdom, 2013. Springer. Plenary Talk. details

51. Sara Silva and Vijay Ingalalli and Susana Vinga and Joao M. B. Carreiras and Joana B. Melo and Mauro Castelli and Leonardo Vanneschi and Ivo Goncalves and Jose Caldas. Prediction of Forest Aboveground Biomass: An Exercise on Avoiding Overfitting. In Anna I. Esparcia-Alcazar and Antonio Della Cioppa and Ivanoe De Falco and Ernesto Tarantino and Carlos Cotta and Robert Schaefer and Konrad Diwold and Kyrre Glette and Andrea Tettamanzi and Alexandros Agapitos and Paolo Burrelli and J. J. Merelo and Stefano Cagnoni and Mengjie Zhang and Neil Urquhart and Kevin Sim and Aniko Ekart and Francisco Fernandez de Vega and Sara Silva and Evert Haasdijk and Gusz Eiben and Anabela Simoes and Philipp Rohlfshagen editors, Applications of Evolutionary Computing, EvoApplications 2013: EvoCOMNET, EvoCOMPLEX, EvoENERGY, EvoFIN, EvoGAMES, EvoIASP, EvoINDUSTRY, EvoNUM, EvoPAR, EvoRISK, EvoROBOT, EvoSTOC, volume 7835, pages 407-417, Vienna, 2013. Springer Verlag. details

52. Mauro Castelli and Sara Silva and Leonardo Vanneschi and Ana Cabral and Maria J. Vasconcelos and Luis Catarino and Joao M. B. Carreiras. Land Cover/Land Use Multiclass Classification Using GP with Geometric Semantic Operators. In Anna I. Esparcia-Alcazar and Antonio Della Cioppa and Ivanoe De Falco and Ernesto Tarantino and Carlos Cotta and Robert Schaefer and Konrad Diwold and Kyrre Glette and Andrea Tettamanzi and Alexandros Agapitos and Paolo Burrelli and J. J. Merelo and Stefano Cagnoni and Mengjie Zhang and Neil Urquhart and Kevin Sim and Aniko Ekart and Francisco Fernandez de Vega and Sara Silva and Evert Haasdijk and Gusz Eiben and Anabela Simoes and Philipp Rohlfshagen editors, Applications of Evolutionary Computing, EvoApplications 2013: EvoCOMNET, EvoCOMPLEX, EvoENERGY, EvoFIN, EvoGAMES, EvoIASP, EvoINDUSTRY, EvoNUM, EvoPAR, EvoRISK, EvoROBOT, EvoSTOC, volume 7835, pages 334-343, Vienna, 2013. Springer Verlag. details

53. Mauro Castelli and Davide Castaldi and Leonardo Vanneschi and Ilaria Giordani and Francesco Archetti and Daniele Maccagnola. An efficient implementation of geometric semantic genetic programming for anticoagulation level prediction in pharmacogenetics. In Christian Blum and Enrique Alba and Thomas Bartz-Beielstein and Daniele Loiacono and Francisco Luna and Joern Mehnen and Gabriela Ochoa and Mike Preuss and Emilia Tantar and Leonardo Vanneschi and Kent McClymont and Ed Keedwell and Emma Hart and Kevin Sim and Steven Gustafson and Ekaterina Vladislavleva and Anne Auger and Bernd Bischl and Dimo Brockhoff and Nikolaus Hansen and Olaf Mersmann and Petr Posik and Heike Trautmann and Muhammad Iqbal and Kamran Shafi and Ryan Urbanowicz and Stefan Wagner and Michael Affenzeller and David Walker and Richard Everson and Jonathan Fieldsend and Forrest Stonedahl and William Rand and Stephen L. Smith and Stefano Cagnoni and Robert M. Patton and Gisele L. Pappa and John Woodward and Jerry Swan and Krzysztof Krawiec and Alexandru-Adrian Tantar and Peter A. N. Bosman and Miguel Vega-Rodriguez and Jose M. Chaves-Gonzalez and David L. Gonzalez-Alvarez and Sergio Santander-Jimenez and Lee Spector and Maarten Keijzer and Kenneth Holladay and Tea Tusar and Boris Naujoks editors, GECCO '13 Companion: Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation conference companion, pages 137-138, Amsterdam, The Netherlands, 2013. ACM. details

54. Mauro Castelli and Davide Castaldi and Ilaria Giordani and Sara Silva and Leonardo Vanneschi and Francesco Archetti and Daniele Maccagnola. An Efficient Implementation of Geometric Semantic Genetic Programming for Anticoagulation Level Prediction in Pharmacogenetics. In Luis Correia and Luis Paulo Reis and Jose Cascalho editors, Proceedings of the 16th Portuguese Conference on Artificial Intelligence, EPIA 2013, volume 8154, pages 78-89, Angra do Heroismo, Azores, Portugal, 2013. Springer. details

55. Leonardo Vanneschi and Matteo Mondini and Martino Bertoni and Alberto Ronchi and Mattia Stefano. GeNet: A Graph-Based Genetic Programming Framework for the Reverse Engineering of Gene Regulatory Networks. In Mario Giacobini and Leonardo Vanneschi and William S. Bush editors, 10th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2012, volume 7246, pages 97-109, Malaga, Spain, 2012. Springer Verlag. details

56. James McDermott and David R. White and Sean Luke and Luca Manzoni and Mauro Castelli and Leonardo Vanneschi and Wojciech Jaskowski and Krzysztof Krawiec and Robin Harper and Kenneth De Jong and Una-May O'Reilly. Genetic programming needs better benchmarks. In Terry Soule and Anne Auger and Jason Moore and David Pelta and Christine Solnon and Mike Preuss and Alan Dorin and Yew-Soon Ong and Christian Blum and Dario Landa Silva and Frank Neumann and Tina Yu and Aniko Ekart and Will Browne and Tim Kovacs and Man-Leung Wong and Clara Pizzuti and Jon Rowe and Tobias Friedrich and Giovanni Squillero and Nicolas Bredeche and Stephen L. Smith and Alison Motsinger-Reif and Jose Lozano and Martin Pelikan and Silja Meyer-Nienberg and Christian Igel and Greg Hornby and Rene Doursat and Steve Gustafson and Gustavo Olague and Shin Yoo and John Clark and Gabriela Ochoa and Gisele Pappa and Fernando Lobo and Daniel Tauritz and Jurgen Branke and Kalyanmoy Deb editors, GECCO '12: Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference, pages 791-798, Philadelphia, Pennsylvania, USA, 2012. ACM. Winner GECCO 2022 ten year impact award. details

57. Mauro Castelli and Luca Manzoni and Leonardo Vanneschi. Parameter tuning of evolutionary reactions systems. In Terry Soule and Anne Auger and Jason Moore and David Pelta and Christine Solnon and Mike Preuss and Alan Dorin and Yew-Soon Ong and Christian Blum and Dario Landa Silva and Frank Neumann and Tina Yu and Aniko Ekart and Will Browne and Tim Kovacs and Man-Leung Wong and Clara Pizzuti and Jon Rowe and Tobias Friedrich and Giovanni Squillero and Nicolas Bredeche and Stephen L. Smith and Alison Motsinger-Reif and Jose Lozano and Martin Pelikan and Silja Meyer-Nienberg and Christian Igel and Greg Hornby and Rene Doursat and Steve Gustafson and Gustavo Olague and Shin Yoo and John Clark and Gabriela Ochoa and Gisele Pappa and Fernando Lobo and Daniel Tauritz and Jurgen Branke and Kalyanmoy Deb editors, GECCO '12: Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference, pages 727-734, Philadelphia, Pennsylvania, USA, 2012. ACM. details

58. Leonardo Trujillo and Sara Silva and Pierrick Legrand and Leonardo Vanneschi. An empirical study of functional complexity as an indicator of overfitting in Genetic Programming. In Sara Silva and James A. Foster and Miguel Nicolau and Mario Giacobini and Penousal Machado editors, Proceedings of the 14th European Conference on Genetic Programming, EuroGP 2011, volume 6621, pages 262-273, Turin, Italy, 2011. Springer Verlag. details

59. James McDermott and Una-May O'Reilly and Leonardo Vanneschi and Kalyan Veeramachaneni. How Far Is It From Here to There? A Distance that is Coherent with GP Operators. In Sara Silva and James A. Foster and Miguel Nicolau and Mario Giacobini and Penousal Machado editors, Proceedings of the 14th European Conference on Genetic Programming, EuroGP 2011, volume 6621, pages 190-202, Turin, Italy, 2011. Springer Verlag. details

60. Mauro Castelli and Luca Manzoni and Leonardo Vanneschi. Multi Objective Genetic Programming for Feature Construction in Classification Problems. In Carlos A. Coello Coello editor, 5th International Conference Learning and Intelligent Optimization (LION 2011), volume 6683, pages 503-506, Rome, Italy, 2011. Selected Papers. details

61. Mauro Castelli and Luca Manzoni and Sara Silva and Leonardo Vanneschi. A Quantitative Study of Learning and Generalization in Genetic Programming. In Sara Silva and James A. Foster and Miguel Nicolau and Mario Giacobini and Penousal Machado editors, Proceedings of the 14th European Conference on Genetic Programming, EuroGP 2011, volume 6621, pages 25-36, Turin, Italy, 2011. Springer Verlag. details

62. Leonardo Vanneschi and Mauro Castelli and Luca Manzoni. The K landscapes: a tunably difficult benchmark for genetic programming. In Natalio Krasnogor and Pier Luca Lanzi and Andries Engelbrecht and David Pelta and Carlos Gershenson and Giovanni Squillero and Alex Freitas and Marylyn Ritchie and Mike Preuss and Christian Gagne and Yew Soon Ong and Guenther Raidl and Marcus Gallager and Jose Lozano and Carlos Coello-Coello and Dario Landa Silva and Nikolaus Hansen and Silja Meyer-Nieberg and Jim Smith and Gus Eiben and Ester Bernado-Mansilla and Will Browne and Lee Spector and Tina Yu and Jeff Clune and Greg Hornby and Man-Leung Wong and Pierre Collet and Steve Gustafson and Jean-Paul Watson and Moshe Sipper and Simon Poulding and Gabriela Ochoa and Marc Schoenauer and Carsten Witt and Anne Auger editors, GECCO '11: Proceedings of the 13th annual conference on Genetic and evolutionary computation, pages 1467-1474, Dublin, Ireland, 2011. ACM. details

63. Leonardo Vanneschi. Fitness landscapes and problem hardness in genetic programming. In Una-May O'Reilly editor, GECCO 2010 Specialized techniques and applications tutorials, pages 2711-2738, Portland, Oregon, USA, 2010. ACM. details

64. Leonardo Vanneschi and Mauro Castelli and Sara Silva. Measuring bloat, overfitting and functional complexity in genetic programming. In Juergen Branke and Martin Pelikan and Enrique Alba and Dirk V. Arnold and Josh Bongard and Anthony Brabazon and Juergen Branke and Martin V. Butz and Jeff Clune and Myra Cohen and Kalyanmoy Deb and Andries P Engelbrecht and Natalio Krasnogor and Julian F. Miller and Michael O'Neill and Kumara Sastry and Dirk Thierens and Jano van Hemert and Leonardo Vanneschi and Carsten Witt editors, GECCO '10: Proceedings of the 12th annual conference on Genetic and evolutionary computation, pages 877-884, Portland, Oregon, USA, 2010. ACM. details

65. Leonardo Vanneschi and Antonella Farinaccio and Mario Giacobini and Marco Antoniotti and Giancarlo Mauri and Paolo Provero. Identification of Individualized Feature Combinations for Survival Prediction in Breast Cancer: A Comparison of Machine Learning Techniques. In Clara Pizzuti and Marylyn D. Ritchie and Mario Giacobini editors, 8th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2010, volume 6023, pages 110-121, Istanbul, 2010. Springer. details

66. Sara Silva and Leonardo Vanneschi. State-of-the-Art Genetic Programming for Predicting Human Oral Bioavailability of Drugs. In Miguel Rocha and Florentino Riverola and Hagit Shatkay and Juan Corchado editors, 4th International Workshop on Practical Applications of Computational Biology and Bioinformatics 2010 (IWPACBB 2010), volume 74, pages 165-173, Guimar\~aes, Portugal, 2010. Springer. details

67. Antonella Farinaccio and Leonardo Vanneschi and Mario Giacobini and Giancarlo Mauri and Paolo Provero. On the use of genetic programming for the prediction of survival in cancer. In Juergen Branke and Martin Pelikan and Enrique Alba and Dirk V. Arnold and Josh Bongard and Anthony Brabazon and Juergen Branke and Martin V. Butz and Jeff Clune and Myra Cohen and Kalyanmoy Deb and Andries P Engelbrecht and Natalio Krasnogor and Julian F. Miller and Michael O'Neill and Kumara Sastry and Dirk Thierens and Jano van Hemert and Leonardo Vanneschi and Carsten Witt editors, GECCO '10: Proceedings of the 12th annual conference on Genetic and evolutionary computation, pages 163-170, Portland, Oregon, USA, 2010. ACM. details

68. Mauro Castelli and Luca Manzoni and Sara Silva and Leonardo Vanneschi. A comparison of the generalization ability of different genetic programming frameworks. In IEEE Congress on Evolutionary Computation (CEC 2010), Barcelona, Spain, 2010. IEEE Press. details

69. Leonardo Vanneschi and Giuseppe Cuccu. A Study of Genetic Programming Variable Population Size for Dynamic Optimization Problems. In Antonio Dourado and Agostinho Rosa and Kurosh Madani editors, International Conference on Evolutionary Computation (ICEC 2009), pages 119-126, Madeira, Portugal, 2009. SciTePress. details

70. Leonardo Vanneschi and Steven Gustafson. Using crossover based similarity measure to improve genetic programming generalization ability. In Guenther Raidl and Franz Rothlauf and Giovanni Squillero and Rolf Drechsler and Thomas Stuetzle and Mauro Birattari and Clare Bates Congdon and Martin Middendorf and Christian Blum and Carlos Cotta and Peter Bosman and Joern Grahl and Joshua Knowles and David Corne and Hans-Georg Beyer and Ken Stanley and Julian F. Miller and Jano van Hemert and Tom Lenaerts and Marc Ebner and Jaume Bacardit and Michael O'Neill and Massimiliano Di Penta and Benjamin Doerr and Thomas Jansen and Riccardo Poli and Enrique Alba editors, GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation, pages 1139-1146, Montreal, 2009. ACM. details

71. Leonardo Vanneschi and Giuseppe Cuccu. Variable size population for dynamic optimization with genetic programming. In Guenther Raidl and Franz Rothlauf and Giovanni Squillero and Rolf Drechsler and Thomas Stuetzle and Mauro Birattari and Clare Bates Congdon and Martin Middendorf and Christian Blum and Carlos Cotta and Peter Bosman and Joern Grahl and Joshua Knowles and David Corne and Hans-Georg Beyer and Ken Stanley and Julian F. Miller and Jano van Hemert and Tom Lenaerts and Marc Ebner and Jaume Bacardit and Michael O'Neill and Massimiliano Di Penta and Benjamin Doerr and Thomas Jansen and Riccardo Poli and Enrique Alba editors, GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation, pages 1895-1896, Montreal, 2009. ACM. details

72. Sara Silva and Leonardo Vanneschi. Operator equalisation, bloat and overfitting: a study on human oral bioavailability prediction. In Guenther Raidl and Franz Rothlauf and Giovanni Squillero and Rolf Drechsler and Thomas Stuetzle and Mauro Birattari and Clare Bates Congdon and Martin Middendorf and Christian Blum and Carlos Cotta and Peter Bosman and Joern Grahl and Joshua Knowles and David Corne and Hans-Georg Beyer and Ken Stanley and Julian F. Miller and Jano van Hemert and Tom Lenaerts and Marc Ebner and Jaume Bacardit and Michael O'Neill and Massimiliano Di Penta and Benjamin Doerr and Thomas Jansen and Riccardo Poli and Enrique Alba editors, GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation, pages 1115-1122, Montreal, 2009. ACM. details

73. Leonardo Vanneschi and Sara Silva. Using Operator Equalisation for Prediction of Drug Toxicity with Genetic Programming. In Luis Seabra Lopes and Nuno Lau and Pedro Mariano and Luis Mateus Rocha editors, Progress in Artificial Intelligence, 14th Portuguese Conference on Artificial Intelligence, EPIA 2009, volume 5816, pages 65-76, Aveiro, Portugal, 2009. Springer. details

74. Riccardo Poli and Nicholas F. McPhee and Leonardo Vanneschi. The impact of population size on code growth in GP: analysis and empirical validation. In Maarten Keijzer and Giuliano Antoniol and Clare Bates Congdon and Kalyanmoy Deb and Benjamin Doerr and Nikolaus Hansen and John H. Holmes and Gregory S. Hornby and Daniel Howard and James Kennedy and Sanjeev Kumar and Fernando G. Lobo and Julian Francis Miller and Jason Moore and Frank Neumann and Martin Pelikan and Jordan Pollack and Kumara Sastry and Kenneth Stanley and Adrian Stoica and El-Ghazali Talbi and Ingo Wegener editors, GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation, pages 1275-1282, Atlanta, GA, USA, 2008. ACM. details

75. Riccardo Poli and Nicholas Freitag McPhee and Leonardo Vanneschi. Elitism reduces bloat in genetic programming. In Maarten Keijzer and Giuliano Antoniol and Clare Bates Congdon and Kalyanmoy Deb and Benjamin Doerr and Nikolaus Hansen and John H. Holmes and Gregory S. Hornby and Daniel Howard and James Kennedy and Sanjeev Kumar and Fernando G. Lobo and Julian Francis Miller and Jason Moore and Frank Neumann and Martin Pelikan and Jordan Pollack and Kumara Sastry and Kenneth Stanley and Adrian Stoica and El-Ghazali Talbi and Ingo Wegener editors, GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation, pages 1343-1344, Atlanta, GA, USA, 2008. ACM. details

76. Francesco Archetti and Mauro Castelli and Ilaria Giordani and Leonardo Vanneschi. Classification of colon tumor tissues using genetic programming. In J. Roberto Serra and Marco Villani and Irene Poli editors, Artificial Life and Evolutionary Computation: Proceedings of Wivace 2008, pages 49-58, Venice, Italy, 2008. World Scientific Publishing Co.. details

77. Leonardo Vanneschi and Marco Tomassini and Philippe Collard and S\'ebastien Verel and Yuri Pirola and Giancarlo Mauri. A Comprehensive View of Fitness Landscapes with Neutrality and Fitness Clouds. In Marc Ebner and Michael O'Neill and Anik\'o Ek\'art and Leonardo Vanneschi and Anna Isabel Esparcia-Alc\'azar editors, Proceedings of the 10th European Conference on Genetic Programming, volume 4445, pages 241-250, Valencia, Spain, 2007. Springer. details

78. Francesco Archetti and Stefano Lanzeni and Enza Messina and Leonardo Vanneschi. Genetic Programming and Other Machine Learning Approaches to Predict Median Oral Lethal Dose (LD50) and Plasma Protein Binding Levels (%PPB) of Drugs. In Elena Marchiori and Jason H. Moore and Jagath C. Rajapakse editors, EvoBIO 2007, Proceedings of the 5th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, volume 4447, pages 11-23, Valencia, Spain, 2007. Springer. details

79. Leonardo Vanneschi and Denis Rochat and Marco Tomassini. Multi-optimization improves genetic programming generalization ability. In Dirk Thierens and Hans-Georg Beyer and Josh Bongard and Jurgen Branke and John Andrew Clark and Dave Cliff and Clare Bates Congdon and Kalyanmoy Deb and Benjamin Doerr and Tim Kovacs and Sanjeev Kumar and Julian F. Miller and Jason Moore and Frank Neumann and Martin Pelikan and Riccardo Poli and Kumara Sastry and Kenneth Owen Stanley and Thomas Stutzle and Richard A Watson and Ingo Wegener editors, GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation, volume 2, pages 1759-1759, London, 2007. ACM Press. details

80. Leonardo Vanneschi and Sebastien Verel. Fitness landscapes and problem hardness in evolutionary computation. In Aniko Ekart editor, Genetic and Evolutionary Computation Conference (GECCO2007) tutorial presentations, pages 3690-3733, London, United Kingdom, 2007. ACM Press. details

81. Leonardo Vanneschi and Marco Tomassini and Philippe Collard and S\'ebastien V\'erel. Negative Slope Coefficient. A Measure to Characterize Genetic Programming. In Pierre Collet and Marco Tomassini and Marc Ebner and Steven Gustafson and Anik\'o Ek\'art editors, Proceedings of the 9th European Conference on Genetic Programming, volume 3905, pages 178-189, Budapest, Hungary, 2006. Springer. details

82. Leonardo Vanneschi and Steven Gustafson and Giancarlo Mauri. Using Subtree Crossover Distance to Investigate Genetic Programming Dynamics. In Pierre Collet and Marco Tomassini and Marc Ebner and Steven Gustafson and Anik\'o Ek\'art editors, Proceedings of the 9th European Conference on Genetic Programming, volume 3905, pages 238-249, Budapest, Hungary, 2006. Springer. details

83. Leonardo Vanneschi and Yuri Pirola and Philippe Collard. A Quantitative Study of Neutrality in GP Boolean Landscapes. In Maarten Keijzer and Mike Cattolico and Dirk Arnold and Vladan Babovic and Christian Blum and Peter Bosman and Martin V. Butz and Carlos Coello Coello and Dipankar Dasgupta and Sevan G. Ficici and James Foster and Arturo Hernandez-Aguirre and Greg Hornby and Hod Lipson and Phil McMinn and Jason Moore and Guenther Raidl and Franz Rothlauf and Conor Ryan and Dirk Thierens editors, GECCO 2006: Proceedings of the 8th annual conference on Genetic and evolutionary computation, volume 1, pages 895-902, Seattle, Washington, USA, 2006. ACM Press. details

84. Leonardo Vanneschi and Giancarlo Mauri and Andrea Valsecchi and Stefano Cagnoni. Heterogeneous cooperative coevolution: strategies of integration between GP and GA. In Maarten Keijzer and Mike Cattolico and Dirk Arnold and Vladan Babovic and Christian Blum and Peter Bosman and Martin V. Butz and Carlos Coello Coello and Dipankar Dasgupta and Sevan G. Ficici and James Foster and Arturo Hernandez-Aguirre and Greg Hornby and Hod Lipson and Phil McMinn and Jason Moore and Guenther Raidl and Franz Rothlauf and Conor Ryan and Dirk Thierens editors, GECCO 2006: Proceedings of the 8th annual conference on Genetic and evolutionary computation, volume 1, pages 361-368, Seattle, Washington, USA, 2006. ACM Press. details

85. Francesco Archetti and Stefano Lanzeni and Enza Messina and Leonardo Vanneschi. Genetic programming for human oral bioavailability of drugs. In Maarten Keijzer and Mike Cattolico and Dirk Arnold and Vladan Babovic and Christian Blum and Peter Bosman and Martin V. Butz and Carlos Coello Coello and Dipankar Dasgupta and Sevan G. Ficici and James Foster and Arturo Hernandez-Aguirre and Greg Hornby and Hod Lipson and Phil McMinn and Jason Moore and Guenther Raidl and Franz Rothlauf and Conor Ryan and Dirk Thierens editors, GECCO 2006: Proceedings of the 8th annual conference on Genetic and evolutionary computation, volume 1, pages 255-262, Seattle, Washington, USA, 2006. ACM Press. details

86. Denis Rochat and Marco Tomassini and Leonardo Vanneschi. Dynamic Size Populations in Distributed Genetic Programming. In Maarten Keijzer and Andrea Tettamanzi and Pierre Collet and Jano I. van Hemert and Marco Tomassini editors, Proceedings of the 8th European Conference on Genetic Programming, volume 3447, pages 50-61, Lausanne, Switzerland, 2005. Springer. details

87. Steven Gustafson and Leonardo Vanneschi. Operator-Based Distance for Genetic Programming: Subtree Crossover Distance. In Maarten Keijzer and Andrea Tettamanzi and Pierre Collet and Jano I. van Hemert and Marco Tomassini editors, Proceedings of the 8th European Conference on Genetic Programming, volume 3447, pages 178-189, Lausanne, Switzerland, 2005. Springer. details

88. Leonardo Vanneschi and Marco Tomassini and Philippe Collard and Manuel Clergue. A Survey of Problem Difficulty in Genetic Programming. In Stefania Bandini and Sara Manzoni editors, AI*IA 2005: Advances in Artificial Intelligence, 9th Congress of the Italian Association for Artificial Intelligence, Proceedings, volume 3673, pages 66-77, Milan, Italy, 2005. Springer. details

89. Leonardo Vanneschi and Manuel Clergue and Philippe Collard and Marco Tomassini and S\'ebastien V\'erel. Fitness Clouds and Problem Hardness in Genetic Programming. In Kalyanmoy Deb and Riccardo Poli and Wolfgang Banzhaf and Hans-Georg Beyer and Edmund Burke and Paul Darwen and Dipankar Dasgupta and Dario Floreano and James Foster and Mark Harman and Owen Holland and Pier Luca Lanzi and Lee Spector and Andrea Tettamanzi and Dirk Thierens and Andy Tyrrell editors, Genetic and Evolutionary Computation -- GECCO-2004, Part II, volume 3103, pages 690-701, Seattle, WA, USA, 2004. Springer-Verlag. details

90. Marco Tomassini and Leonardo Vanneschi and Jerome Cuendet and Francisco Fernandez. A New Technique for Dynamic Size Populations in Genetic Programming. In Proceedings of the 2004 IEEE Congress on Evolutionary Computation, pages 486-493, Portland, Oregon, 2004. IEEE Press. details

91. Leonardo Vanneschi and Marco Tomassini and Manuel Clergue and Philippe Collard. Difficulty of Unimodal and Multimodal Landscapes in Genetic Programming. In E. Cant\'u-Paz and J. A. Foster and K. Deb and D. Davis and R. Roy and U.-M. O'Reilly and H.-G. Beyer and R. Standish and G. Kendall and S. Wilson and M. Harman and J. Wegener and D. Dasgupta and M. A. Potter and A. C. Schultz and K. Dowsland and N. Jonoska and J. Miller editors, Genetic and Evolutionary Computation -- GECCO-2003, volume 2724, pages 1788-1799, Chicago, 2003. Springer-Verlag. details

92. L. Vanneschi and M. Tomassini and P. Collard and M. Clergue. Fitness distance correlation in genetic programming: A constructive counterexample. In Ruhul Sarker and Robert Reynolds and Hussein Abbass and Kay Chen Tan and Bob McKay and Daryl Essam and Tom Gedeon editors, Proceedings of the 2003 Congress on Evolutionary Computation CEC2003, pages 289-296, Canberra, 2003. IEEE Press. details

93. Leonardo Vanneschi and Marco Tomassini and Philippe Collard and Manuel Clergue. Fitness Distance Correlation in Structural Mutation Genetic Programming. In Conor Ryan and Terence Soule and Maarten Keijzer and Edward Tsang and Riccardo Poli and Ernesto Costa editors, Genetic Programming, Proceedings of EuroGP'2003, volume 2610, pages 455-464, Essex, 2003. Springer-Verlag. details

94. Leonardo Vanneschi and Marco Tomassini. Pros and Cons of Fitness Distance Correlation in Genetic Programming. In Alwyn M. Barry editor, GECCO 2003: Proceedings of the Bird of a Feather Workshops, Genetic and Evolutionary Computation Conference, pages 284-287, Chigaco, 2003. AAAI. details

95. Marco Tomassini and Leonardo Vanneschi and Francisco Fern\'andez and Germ\'an Galeano. Diversity in Multipopulation Genetic Programming. In E. Cant\'u-Paz and J. A. Foster and K. Deb and D. Davis and R. Roy and U.-M. O'Reilly and H.-G. Beyer and R. Standish and G. Kendall and S. Wilson and M. Harman and J. Wegener and D. Dasgupta and M. A. Potter and A. C. Schultz and K. Dowsland and N. Jonoska and J. Miller editors, Genetic and Evolutionary Computation -- GECCO-2003, volume 2724, pages 1812-1813, Chicago, 2003. Springer-Verlag. details

96. Marco Tomassini and Leonardo Vanneschi and Francisco Fernandez and German Galeano. A Study of Diversity in Multipopulation Genetic Programming. In Pierre Liardet and Pierre Collet and Cyril Fonlupt and Evelyne Lutton and Marc Schoenauer editors, Evolution Artificielle, 6th International Conference, volume 2936, pages 243-255, Marseilles, France, 2003. Springer. Revised Selected Papers. details

97. G. Folino and C. Pizzuti and G. Spezzano and L. Vanneschi and M. Tomassini. Diversity analysis in cellular and multipopulation genetic programming. In Ruhul Sarker and Robert Reynolds and Hussein Abbass and Kay Chen Tan and Bob McKay and Daryl Essam and Tom Gedeon editors, Proceedings of the 2003 Congress on Evolutionary Computation CEC2003, pages 305-311, Canberra, 2003. IEEE Press. details

98. F. Fernandez and M. Tomassini and L. Vanneschi. Saving computational effort in genetic programming by means of plagues. In Ruhul Sarker and Robert Reynolds and Hussein Abbass and Kay Chen Tan and Bob McKay and Daryl Essam and Tom Gedeon editors, Proceedings of the 2003 Congress on Evolutionary Computation CEC2003, pages 2042-2049, Canberra, 2003. IEEE Press. details

99. Francisco Fernandez and Leonardo Vanneschi and Marco Tomassini. The Effect of Plagues in Genetic Programming: A Study of Variable-Size Populations. In Conor Ryan and Terence Soule and Maarten Keijzer and Edward Tsang and Riccardo Poli and Ernesto Costa editors, Genetic Programming, Proceedings of EuroGP'2003, volume 2610, pages 317-326, Essex, 2003. Springer-Verlag. details

100. Leonardo Vanneschi and Marco Tomassini. A Study on Fitness Distance Correlation and Problem Difficulty for Genetic Programming. In Sean Luke and Conor Ryan and Una-May O'Reilly editors, Graduate Student Workshop, pages 307-310, New York, 2002. AAAI. details

101. Marco Tomassini and Leonardo Vanneschi and Francisco Fernandez and German Galeano. Experimental Investigation Of Three Distributed Genetic Programming Models. In Juan J. Merelo-Guervos and Panagiotis Adamidis and Hans-Georg Beyer and Jose-Luis Fernandez-Villacanas and Hans-Paul Schwefel editors, Parallel Problem Solving from Nature - PPSN VII, pages 641-650, Granada, Spain, 2002. Springer-Verlag. details

102. Mario Giacobini and Marco Tomassini and Leonardo Vanneschi. Limiting the Number of Fitness Cases in Genetic Programming Using Statistics. In Juan J. Merelo-Guervos and Panagiotis Adamidis and Hans-Georg Beyer and Jose-Luis Fernandez-Villacanas and Hans-Paul Schwefel editors, Parallel Problem Solving from Nature - PPSN VII, pages 371-380, Granada, Spain, 2002. Springer-Verlag. details

103. Mario Giacobini and Marco Tomassini and Leonardo Vanneschi. How Statistics Can Help In Limiting The Number Of Fitness Cases In Genetic Programming. In W. B. Langdon and E. Cant\'u-Paz and K. Mathias and R. Roy and D. Davis and R. Poli and K. Balakrishnan and V. Honavar and G. Rudolph and J. Wegener and L. Bull and M. A. Potter and A. C. Schultz and J. F. Miller and E. Burke and N. Jonoska editors, GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference, page 889, New York, 2002. Morgan Kaufmann Publishers. details

104. G. Galeano and F. Fernandez and M. Tomassini and L. Vanneschi. Studying the influence of Synchronous and Asynchronous parallel GP on Programs' Length Evolution. In David B. Fogel and Mohamed A. El-Sharkawi and Xin Yao and Garry Greenwood and Hitoshi Iba and Paul Marrow and Mark Shackleton editors, Proceedings of the 2002 Congress on Evolutionary Computation CEC2002, pages 1727-1732, Honolulu, USA, 2002. IEEE Press. details

105. Manuel Clergue and Philippe Collard and Marco Tomassini and Leonardo Vanneschi. Fitness Distance Correlation And Problem Difficulty For Genetic Programming. In W. B. Langdon and E. Cant\'u-Paz and K. Mathias and R. Roy and D. Davis and R. Poli and K. Balakrishnan and V. Honavar and G. Rudolph and J. Wegener and L. Bull and M. A. Potter and A. C. Schultz and J. F. Miller and E. Burke and N. Jonoska editors, GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference, pages 724-732, New York, 2002. Morgan Kaufmann Publishers. details

106. Francisco Fernandez and Marco Tomassini and Leonardo Vanneschi. Studying the Influence of Communication Topology and Migration on Distributed Genetic Programming. In Julian F. Miller and Marco Tomassini and Pier Luca Lanzi and Conor Ryan and Andrea G. B. Tettamanzi and William B. Langdon editors, Genetic Programming, Proceedings of EuroGP'2001, volume 2038, pages 51-63, Lake Como, Italy, 2001. Springer-Verlag. details

107. Francisco Fernandez and Marco Tomassini and Leonardo Vanneschi and Laurent Bucher. A Distributed Computing Environment for Genetic Programming using MPI. In Jack J. Dongarra and Peter Kacsuk and Norbert Podhorszki editors, Recent advances in parallel virtual machine and message passing interface: 7th European PVM\slash MPI Users' Group Meeting, volume 1908, pages 322-329, Balatonfured, Hungary, 2000. Springer-Verlag. details

Genetic Programming book chapters by Leonardo Vanneschi

1. Marco Giacobini and Paolo Provero and Leonardo Vanneschi and Giancarlo Mauri. Towards the Use of Genetic Programming for the Prediction of Survival in Cancer. In Stefano Cagnoni and Marco Mirolli and Marco Villani editors, Evolution, Complexity and Artificial Life, pages 177-192. Springer, 2014. details

2. Leonardo Vanneschi and Sara Silva and Mauro Castelli and Luca Manzoni. Geometric Semantic Genetic Programming for Real Life Applications. In Rick Riolo and Jason H. Moore and Mark Kotanchek editors, Genetic Programming Theory and Practice XI, chapter 11, pages 191-209. Springer, Ann Arbor, USA, 2013. details

3. Leonardo Vanneschi and Riccardo Poli. Genetic Programming: Introduction, Applications, Theory and Open Issues. In Grzegorz Rozenberg and Thomas Baeck and Joost N. Kok editors, Handbook of Natural Computing, volume 2, chapter 24, pages 709-739. Springer, 2012. details

4. Sara Silva and Leonardo Vanneschi. The Importance of Being Flat-Studying the Program Length Distributions of Operator Equalisation. In Rick Riolo and Ekaterina Vladislavleva and Jason H. Moore editors, Genetic Programming Theory and Practice IX, chapter 12, pages 211-233. Springer, Ann Arbor, USA, 2011. details

5. Riccardo Poli and Nicholas F. McPhee and Leonardo Vanneschi. Analysis of the Effects of Elitism on Bloat in Linear and Tree-based Genetic Programming. In Rick L. Riolo and Terence Soule and Bill Worzel editors, Genetic Programming Theory and Practice VI, chapter 7, pages 91-111. Springer, Ann Arbor, 2008. details

6. Leonardo Vanneschi. Investigating Problem Hardness of Real Life Applications. In Rick L. Riolo and Terence Soule and Bill Worzel editors, Genetic Programming Theory and Practice V, chapter 7, pages 107-125. Springer, Ann Arbor, 2007. details

7. Francisco Fernandez and Giandomenico Spezzano and Marco Tomassini and Leonardo Vanneschi. Parallel Genetic Programming. In Enrique Alba editor, Parallel Metaheuristics, chapter 6, pages 127-153. Wiley-Interscience, Hoboken, New Jersey, USA, 2005. details

Genetic Programming other entries for Leonardo Vanneschi

• Mauro Castelli and Luca Manzoni and Leonardo Vanneschi. An Efficient Genetic Programming System with Geometric Semantic Operators and its Application to Human Oral Bioavailability Prediction. 2012. details