Genetic Programming Algorithms for Dynamic Environments

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{conf/evoW/MacedoCM16,

• author = "Joao Macedo and Ernesto Costa and Lino Marques",
• title = "Genetic Programming Algorithms for Dynamic Environments",
• booktitle = "19th European Conference on Applications of Evolutionary Computation, EvoApplications 2016",
• year = "2016",
• editor = "Giovanni Squillero and Paolo Burelli",
• volume = "9598",
• series = "Lecture Notes in Computer Science",
• pages = "280--295",
• address = "Porto, Portugal",
• month = mar # " 30 -- " # apr # " 1",
• organisation = "EvoStar",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming",
• bibdate = "2016-03-29",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/evoW/evoappl2016-2.html#MacedoCM16",
• isbn13 = "978-3-319-31153-1",
• URL = "http://dx.doi.org/10.1007/978-3-319-31153-1",
• DOI = "doi:10.1007/978-3-319-31153-1_19",
• abstract = "Evolutionary algorithms are a family of stochastic search heuristics that include Genetic Algorithms (GA) and Genetic Programming (GP). Both GAs and GPs have been successful in many applications, mainly with static scenarios. However, many real world applications involve dynamic environments (DE). Many work has been made to adapt GAs to DEs, but only a few efforts in adapting GPs for this kind of environments. In this paper we present novel GP algorithms for dynamic environments and study their performance using three dynamic benchmark problems, from the areas of Symbolic Regression, Classification and Path Planning. Furthermore, we apply the best algorithm we found in the navigation of an Erratic Robot through a dynamic Santa Fe Ant Trail and compare its performance to the standard GP algorithm. The results, statistically validated, are very promising.",
• notes = "EvoApplications2016 held inconjunction with EuroGP'2016, EvoCOP2016 and EvoMUSART 2016",

}

Genetic Programming entries for Joao Macedo Ernesto Costa Lino Marques

Citations