3noA method to increase the generalization ability of genetic programming (GP) is proposed in this paper. The idea consists in giving a second chance of mating to individuals belonging to “old” generations (hence the name of the method: “second chance GP”). Although original, the idea is inspired by well-known concepts such as short-term memory schemes, that have already been used in evolutionary computation so far. Three complex real-life applications characterized by a high dimen- sionality of the space of the features have been used to experimentally validate the approach. These three problems are interesting for our study because in one of them standard GP has no overfitting, in the second one standard GP tends to slightly overfit train...
Tournament selection is the most frequently used form of selection in Genetic Programming (GP). Tour...
Genetic algorithm (i.e., GA) has longtermly obtained an extensive recognition for solving the optimi...
Abstract: In this paper, we study extensions of Genetic Algorithm (GA) to incorporate improved sampl...
3noIn this paper a method to increase the optimization ability of genetic algorithms (GAs) is propos...
Castelli, M., Manzoni, L., Mariot, L., Menara, G., & Pietropolli, G. (2022). The Effect of Multi-Gen...
Genetic programming (GP) is an automated method for creating a working computer program from a high-...
Genetic Algorithms are bio-inspired metaheuristics that solve optimization problems; they are evolut...
Tournament selection is the most frequently used form of selection in genetic programming (GP). Tou...
Genetic Programming is a form of Evolutionary Computation in which computer programs are evolved by ...
The recognition of useful information, its retention in memory, and subsequent use plays an importan...
The ability to generalize beyond the training set is important for Genetic Programming (GP). Interle...
For more than two decades, genetic algorithms (GAs) have been studied by researchers from different ...
4Grammar-guided Genetic Programming (G3P) is a family of Evolutionary Algorithms that can evolve pro...
International audienceThis paper proposes a theoretical analysis of Genetic Programming (GP) from th...
Genetic programming is an automatic programming method that creates computer programs to satisfy a s...
Tournament selection is the most frequently used form of selection in Genetic Programming (GP). Tour...
Genetic algorithm (i.e., GA) has longtermly obtained an extensive recognition for solving the optimi...
Abstract: In this paper, we study extensions of Genetic Algorithm (GA) to incorporate improved sampl...
3noIn this paper a method to increase the optimization ability of genetic algorithms (GAs) is propos...
Castelli, M., Manzoni, L., Mariot, L., Menara, G., & Pietropolli, G. (2022). The Effect of Multi-Gen...
Genetic programming (GP) is an automated method for creating a working computer program from a high-...
Genetic Algorithms are bio-inspired metaheuristics that solve optimization problems; they are evolut...
Tournament selection is the most frequently used form of selection in genetic programming (GP). Tou...
Genetic Programming is a form of Evolutionary Computation in which computer programs are evolved by ...
The recognition of useful information, its retention in memory, and subsequent use plays an importan...
The ability to generalize beyond the training set is important for Genetic Programming (GP). Interle...
For more than two decades, genetic algorithms (GAs) have been studied by researchers from different ...
4Grammar-guided Genetic Programming (G3P) is a family of Evolutionary Algorithms that can evolve pro...
International audienceThis paper proposes a theoretical analysis of Genetic Programming (GP) from th...
Genetic programming is an automatic programming method that creates computer programs to satisfy a s...
Tournament selection is the most frequently used form of selection in Genetic Programming (GP). Tour...
Genetic algorithm (i.e., GA) has longtermly obtained an extensive recognition for solving the optimi...
Abstract: In this paper, we study extensions of Genetic Algorithm (GA) to incorporate improved sampl...