Runtime analysis of mutation-based geometric semantic genetic programming for basis functions regression A Moraglio, A Mambrini Proceedings of the 15th annual conference on Genetic and evolutionary …, 2013 | 34 | 2013 |

PaDe: A parallel algorithm based on the MOEA/D framework and the island model A Mambrini, D Izzo Parallel Problem Solving from Nature–PPSN XIII: 13th International …, 2014 | 24 | 2014 |

Runtime analysis of mutation-based geometric semantic genetic programming on boolean functions A Moraglio, A Mambrini, L Manzoni Proceedings of the twelfth workshop on Foundations of genetic algorithms XII …, 2013 | 23 | 2013 |

Design and analysis of schemes for adapting migration intervals in parallel evolutionary algorithms A Mambrini, D Sudholt Evolutionary computation 23 (4), 559-582, 2015 | 21 | 2015 |

Design and analysis of adaptive migration intervals in parallel evolutionary algorithms A Mambrini, D Sudholt Proceedings of the 2014 annual conference on genetic and evolutionary …, 2014 | 21 | 2014 |

Homogeneous and Heterogeneous Island Models for the Set Cover Problem A Mambrini, D Sudholt, X Yao Parallel Problem Solving from Nature-PPSN XII, 11-20, 2012 | 18 | 2012 |

On the analysis of simple genetic programming for evolving boolean functions A Mambrini, PS Oliveto Genetic Programming: 19th European Conference, EuroGP 2016, Porto, Portugal …, 2016 | 14 | 2016 |

Theory-laden design of mutation-based geometric semantic genetic programming for learning classification trees A Mambrini, L Manzoni, A Moraglio 2013 IEEE Congress on Evolutionary Computation, 416-423, 2013 | 8 | 2013 |

A comparison between geometric semantic GP and cartesian GP for Boolean functions learning A Mambrini, L Manzoni Proceedings of the Companion Publication of the 2014 Annual Conference on …, 2014 | 5 | 2014 |

PRINCIPIA: a decentralized peer-review ecosystem A Mambrini, A Baronchelli, M Starnini, D Marinazzo, M De Domenico arXiv preprint arXiv:2008.09011, 2020 | 1 | 2020 |

Theory grounded design of genetic programming and parallel evolutionary algorithms A Mambrini University of Birmingham, 2015 | | 2015 |

A framework for measuring the generalization ability of Geometric Semantic Genetic Programming (GSGP) for Black-Box Boolean Functions Learning A Mambrini, Y Yu, X Yao | | |