Towards Intelligent Control via Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8010

@InProceedings{Marchetti:2020:IJCNN,

• author = "Francesco Marchetti and Edmondo Minisci and Annalisa Riccardi",
• title = "Towards Intelligent Control via Genetic Programming",
• booktitle = "2020 International Joint Conference on Neural Networks (IJCNN)",
• year = "2020",
• abstract = "In this paper an initial approach to Intelligent Control (IC) using Genetic Programming (GP) for access to space applications is presented. GP can be employed successfully to design a controller even for complex systems, where classical controllers fail because of the high nonlinearity of the systems. The main property of GP, that is its ability to autonomously create explicit mathematical equations starting from a very poor knowledge of the considered plant, or just data, can be exploited for a vast range of applications. Here, GP has been used to design the control law in an Intelligent Control framework for a modified version of the Goddard Rocket problem in 3 different failure scenarios, where the approach to IC consists in an online re-evaluation of the control law using GP when a considerably big change in the environment or in the plant happens. The presented results are then used to highlight the potential benefits of the method, as well as aspects that will need further developments.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/IJCNN48605.2020.9207694",
• ISSN = "2161-4407",
• month = jul,
• notes = "Also known as \cite{9207694}",

}

Genetic Programming entries for Francesco Marchetti Edmondo Minisci Annalisa Riccardi

Citations