16 citations · 25 across the 7 of their papers we have counts for
7 papers · 1 filter
Local Search, Semantics, and Genetic Programming: a Global Analysis
Fabio Anselmi, Mauro Castelli, Alberto d'Onofrio +3
Geometric Semantic Geometric Programming (GSGP) is one of the most prominent Genetic Programming (GP) variants, thanks to its solid theoretical background, the excellent performanc…
The Effect of Multi-Generational Selection in Geometric Semantic Genetic Programming
Mauro Castelli, Luca Manzoni, Luca Mariot +2
Among the evolutionary methods, one that is quite prominent is Genetic Programming, and, in recent years, a variant called Geometric Semantic Genetic Programming (GSGP) has shown t…
GSGP-CUDA -- a CUDA framework for Geometric Semantic Genetic Programming
Leonardo Trujillo, Jose Manuel Muñoz Contreras, Daniel E Hernandez +2
Geometric Semantic Genetic Programming (GSGP) is a state-of-the-art machine learning method based on evolutionary computation. GSGP performs search operations directly at the level…
Salp Swarm Optimization: a Critical Review
Mauro Castelli, Luca Manzoni, Luca Mariot +2
In the crowded environment of bio-inspired population-based metaheuristics, the Salp Swarm Optimization (SSO) algorithm recently appeared and immediately gained a lot of momentum.…
A Distance Between Populations for n-Points Crossover in Genetic Algorithms
Mauro Castelli, Gianpiero Cattaneo, Luca Manzoni +1
Genetic algorithms (GAs) are an optimization technique that has been successfully used on many real-world problems. There exist different approaches to their theoretical study. In…
Unsure When to Stop? Ask Your Semantic Neighbors
Ivo Gonçalves, Sara Silva, Carlos M. Fonseca +1
In iterative supervised learning algorithms it is common to reach a point in the search where no further induction seems to be possible with the available data. If the search is co…