Genetic Programming Bibliography entries for Leo Francoso Dal Piccol Sotto

up to index Created by W.Langdon from gp-bibliography.bib Revision:1.7630

GP coauthors/coeditors: Vinicius Veloso de Melo, Alvaro Luiz Fazenda, Giovanni Iacca, Roman Tobias Kalkreuth, Zdenek Vasicek, Marcio Porto Basgalupp, Regina Celia Coelho, Franz Rothlauf, Paul Kaufmann, Timothy Atkinson,

Genetic Programming Articles by Leo Francoso Dal Piccol Sotto

  1. Leo Francoso Dal Piccol Sotto and Franz Rothlauf and Vinicius Veloso de Melo and Marcio P. Basgalupp. An Analysis of the Influence of Non-effective Instructions in Linear Genetic Programming. Evolutionary Computation, 30(1):51-74, 2022. details

  2. Leo Francoso Dal Piccol Sotto and Paul Kaufmann and Timothy Atkinson and Roman Kalkreuth and Marcio Porto Basgalupp. Graph representations in genetic programming. Genetic Programming and Evolvable Machines, 22(4):607-636, 2021. Special Issue: Highlights of Genetic Programming 2020 Events. details

  3. Leo Francoso Dal Piccol Sotto and Vinicius Veloso de Melo and Marcio Porto Basgalupp. $\lambda$-LGP: an improved version of linear genetic programming evaluated in the Ant Trail problem. Knowledge and Information Systems, 52(2):445-465, 2017. details

  4. Leo Francoso dal Piccol Sotto and Vinicius Veloso de Melo. Studying bloat control and maintenance of effective code in linear genetic programming for symbolic regression. Neurocomputing, 180:79-93, 2016. Progress in Intelligent Systems Design Selected papers from the 4th Brazilian Conference on Intelligent Systems (BRACIS 2014). details

Genetic Programming conference papers by Leo Francoso Dal Piccol Sotto

  1. Roman Kalkreuth and Leo Francoso Dal Piccol Sotto and Zdenek Vasicek. Graph-based genetic programming. In Jonathan E. Fieldsend and Markus Wagner editors, GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9 - 13, 2022, pages 958-982, 2022. ACM. details

  2. Leo Francoso D. P. Sotto and Paul Kaufmann and Timothy Atkinson and Roman Kalkreuth and Marcio Porto Basgalupp. A Study on Graph Representations for 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 931-939, internet, 2020. Association for Computing Machinery. details

  3. Vinicius Veloso de Melo and Alvaro Luiz Fazenda and Leo Francoso Dal Piccol Sotto and Giovanni Iacca. A MIMD Interpreter for Genetic Programming. In Pedro A. Castillo and Juan Luis Jimenez Laredo and Francisco Fernandez de Vega editors, 23rd International Conference, EvoApplications 2020, volume 12104, pages 645-658, Seville, Spain, 2020. Springer Verlag. details

  4. Leo Francoso Dal Piccol Sotto and Franz Rothlauf. On the role of non-effective code in linear genetic programming. In Manuel Lopez-Ibanez and Thomas Stuetzle and Anne Auger and Petr Posik and Leslie Peprez Caceres and Andrew M. Sutton and Nadarajen Veerapen and Christine Solnon and Andries Engelbrecht and Stephane Doncieux and Sebastian Risi and Penousal Machado and Vanessa Volz and Christian Blum and Francisco Chicano and Bing Xue and Jean-Baptiste Mouret and Arnaud Liefooghe and Jonathan Fieldsend and Jose Antonio Lozano and Dirk Arnold and Gabriela Ochoa and Tian-Li Yu and Holger Hoos and Yaochu Jin and Ting Hu and Miguel Nicolau and Robin Purshouse and Thomas Baeck and Justyna Petke and Giuliano Antoniol and Johannes Lengler and Per Kristian Lehre editors, GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference, pages 1075-1083, Prague, Czech Republic, 2019. ACM. details

  5. Leo Francoso Dal Piccol Sotto and Vinicius Veloso de Melo. A Probabilistic Linear Genetic Programming with Stochastic Context-free Grammar for Solving Symbolic Regression Problems. In Proceedings of the Genetic and Evolutionary Computation Conference, pages 1017-1024, Berlin, Germany, 2017. ACM. details

  6. Leo Francoso Dal Piccol Sotto and Vinicius Veloso de Melo and Marcio P. Basgalupp. An improved $\lambda$-linear genetic programming evaluated in solving the Santa Fe ant trail problem. In Sascha Ossowski editor, Proceedings of the 31st Annual ACM Symposium on Applied Computing, pages 103-108, Pisa, Italy, 2016. ACM. details

  7. Leo Francoso Dal Piccol Sotto and Vinicius Veloso de Melo. Solving the Lawn Mower problem with Kaizen Programming and $\lambda$-Linear Genetic Programming for Module Acquisition. In Tobias Friedrich and Frank Neumann and Andrew M. Sutton and Martin Middendorf and Xiaodong Li and Emma Hart and Mengjie Zhang and Youhei Akimoto and Peter A. N. Bosman and Terry Soule and Risto Miikkulainen and Daniele Loiacono and Julian Togelius and Manuel Lopez-Ibanez and Holger Hoos and Julia Handl and Faustino Gomez and Carlos M. Fonseca and Heike Trautmann and Alberto Moraglio and William F. Punch and Krzysztof Krawiec and Zdenek Vasicek and Thomas Jansen and Jim Smith and Simone Ludwig and JJ Merelo and Boris Naujoks and Enrique Alba and Gabriela Ochoa and Simon Poulding and Dirk Sudholt and Timo Koetzing editors, GECCO '16 Companion: Proceedings of the Companion Publication of the 2016 Annual Conference on Genetic and Evolutionary Computation, pages 113-114, Denver, USA, 2016. ACM. details

  8. Leo Francoso Dal Piccol Sotto and Regina Celia Coelho and Vinicius Veloso de Melo. Classification of Cardiac Arrhythmia by Random Forests with Features Constructed by Kaizen Programming using Linear Genetic Programming. In Tobias Friedrich editor, GECCO '16: Proceedings of the 2016 Annual Conference on Genetic and Evolutionary Computation, pages 813-820, Denver, USA, 2016. ACM. details

  9. Leo Francoso Dal Piccol Sotto and Vinicius Veloso de Melo. Comparison of linear genetic programming variants for symbolic regression. In Christian Igel and Dirk V. Arnold and Christian Gagne and Elena Popovici and Anne Auger and Jaume Bacardit and Dimo Brockhoff and Stefano Cagnoni and Kalyanmoy Deb and Benjamin Doerr and James Foster and Tobias Glasmachers and Emma Hart and Malcolm I. Heywood and Hitoshi Iba and Christian Jacob and Thomas Jansen and Yaochu Jin and Marouane Kessentini and Joshua D. Knowles and William B. Langdon and Pedro Larranaga and Sean Luke and Gabriel Luque and John A. W. McCall and Marco A. Montes de Oca and Alison Motsinger-Reif and Yew Soon Ong and Michael Palmer and Konstantinos E. Parsopoulos and Guenther Raidl and Sebastian Risi and Guenther Ruhe and Tom Schaul and Thomas Schmickl and Bernhard Sendhoff and Kenneth O. Stanley and Thomas Stuetzle and Dirk Thierens and Julian Togelius and Carsten Witt and Christine Zarges editors, GECCO Comp '14: Proceedings of the 2014 conference companion on Genetic and evolutionary computation companion, pages 135-136, Vancouver, BC, Canada, 2014. ACM. details

  10. Leo Francoso Dal Piccol Sotto and Vinicius Veloso de Melo. Investigation of Linear Genetic Programming Techniques for Symbolic Regression. In Ricardo B. C. Prudencio and Paulo E. Santos editors, Brazilian Conference on Intelligent Systems, BRACIS 2014, pages 146-151, Sao Paulo, Brazil, 2014. IEEE. details