Genetic Programming Bibliography entries for Andrea Mambrini
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Created by W.Langdon from
Pietro S Oliveto,
Genetic Programming PhD doctoral thesis Andrea Mambrini
Theory grounded design of genetic programming and parallel evolutionary algorithms. PhD thesis,
School of Computer Science, University of Birmingham, UK, 2015.
Genetic Programming conference papers by Andrea Mambrini
Andrea Mambrini and Pietro S. Oliveto.
On the Analysis of Simple Genetic Programming for Evolving Boolean Functions. In
Malcolm I. Heywood and James McDermott and Mauro Castelli and Ernesto Costa and Kevin Sim editors,
EuroGP 2016: Proceedings of the 19th European Conference on Genetic Programming, volume 9594, pages 99-114, Porto, Portugal, 2016. Springer Verlag.
Andrea Mambrini and Yang Yu2 and Xin Yao.
A framework for measuring the generalization ability of Geometric Semantic Genetic Programming (GSGP) for Black-Box Boolean Functions Learning. 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.
Andrea Mambrini and Luca Manzoni.
A comparison between geometric semantic GP and cartesian GP for boolean functions learning. 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 143-144, Vancouver, BC, Canada, 2014. ACM.
Alberto Moraglio and Andrea Mambrini.
Runtime analysis of mutation-based geometric semantic genetic programming for basis functions regression. In
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, pages 989-996, Amsterdam, The Netherlands, 2013. ACM.
Alberto Moraglio and Andrea Mambrini and Luca Manzoni.
Runtime Analysis of Mutation-Based Geometric Semantic Genetic Programming on Boolean Functions. In
Frank Neumann and Kenneth De Jong editors,
Foundations of Genetic Algorithms, pages 119-132, Adelaide, Australia, 2013. ACM.
Andrea Mambrini and Luca Manzoni and Alberto Moraglio.
Theory-Laden Design of Mutation-Based Geometric Semantic Genetic Programming for Learning Classification Trees. In
Luis Gerardo de la Fraga editor,
2013 IEEE Conference on Evolutionary Computation, volume 1, pages 416-423, Cancun, Mexico, 2013.