Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Léo Françoso Dal Piccol Sotto"'
Publikováno v:
Evolutionary Computation. 30:51-74
Linear Genetic Programming (LGP) represents programs as sequences of instructions and has a Directed Acyclic Graph (DAG) dataflow. The results of instructions are stored in registers that can be used as arguments by other instructions. Instructions t
Publikováno v:
Proceedings of the Genetic and Evolutionary Computation Conference Companion.
Publikováno v:
Proceedings of the Genetic and Evolutionary Computation Conference Companion.
Autor:
Fabio Augusto Faria, Matheus Macedo Leonardo, Vinícius Veloso de Melo, Léo Françoso Dal Piccol Sotto
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 17:1652-1656
The aerial scene-classification task is a challenging problem to remote sensing area with important applicability to civil and military affairs. A technique that has achieved excellent results in this task is the convolutional neural network (CNN). C
Autor:
Márcio P. Basgalupp, Paul Kaufmann, Roman Kalkreuth, Léo Françoso Dal Piccol Sotto, Timothy Atkinson
Graph representations promise several desirable properties for genetic programming (GP); multiple-output programs, natural representations of code reuse and, in many cases, an innate mechanism for neutral drift. Each graph GP technique provides a pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8b895afa8f47274fe18d3ec68305548a
https://publica.fraunhofer.de/handle/publica/270605
https://publica.fraunhofer.de/handle/publica/270605
Autor:
Paul Kaufmann, Márcio P. Basgalupp, Roman Kalkreuth, Timothy Atkinson, Léo Françoso Dal Piccol Sotto
Publikováno v:
GECCO
Graph representations promise several desirable properties for Genetic Programming (GP); multiple-output programs, natural representations of code reuse and, in many cases, an innate mechanism for neutral drift. Each graph GP technique provides a pro
Publikováno v:
Applications of Evolutionary Computation ISBN: 9783030437213
EvoApplications
EvoApplications
Most Genetic Programming implementations use an interpreter to execute an individual, in order to obtain its outcome. Usually, such interpreter is the main bottleneck of the algorithm, since a single individual may contain thousands of instructions t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5bff9c599bbf8b9642dd15c8b4a7bb1b
https://link.springer.com/chapter/10.1007/978-3-030-43722-0_41
https://link.springer.com/chapter/10.1007/978-3-030-43722-0_41
Publikováno v:
Knowledge and Information Systems. 52:445-465
The Ant Trail problem has been widely investigated as a benchmark for automatic design of algorithms. One must design the program of a virtual ant to collect all pieces of food located in different places of a map, which may have obstacles, in a pred
Publikováno v:
GECCO
In linear variants of Genetic Programming (GP) like linear genetic programming (LGP), structural introns can emerge, which are nodes that are not connected to the final output and do not contribute to the output of a program. There are claims that su
Publikováno v:
Neurocomputing. 180:79-93
Linear Genetic Programming (LGP) is an Evolutionary Computation algorithm, inspired in the Genetic Programming (GP) algorithm. Instead of using the standard tree representation of GP, LGP evolves a linear program, which causes a graph-based data flow