Genetic Programming: Introduction, Applications, Theory and Open Issues

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

@InCollection{VanneschiPoliHNC2011,

• author = "Leonardo Vanneschi and Riccardo Poli",
• title = "Genetic Programming: Introduction, Applications, Theory and Open Issues",
• booktitle = "Handbook of Natural Computing",
• publisher = "Springer",
• year = "2012",
• editor = "Grzegorz Rozenberg and Thomas Baeck and Joost N. Kok",
• volume = "2",
• chapter = "24",
• pages = "709--739",
• month = "19 " # aug,
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-540-92909-3",
• URL = "http://cswww.essex.ac.uk/staff/poli/papers/VanneschiPoliHNC2011.pdf",
• URL = "http://www.springer.com/computer/theoretical+computer+science/book/978-3-540-92911-6",
• DOI = "doi:10.1007/978-3-540-92910-9_24",
• abstract = "Genetic programming (GP) is an evolutionary approach that extends genetic algorithms to allow the exploration of the space of computer programs. Like other evolutionary algorithms, GP works by defining a goal in the form of a quality criterion (or fitness) and then using this criterion to evolve a set (or population) of candidate solutions (individuals) by mimicking the basic principles of Darwinian evolution. GP breeds the solutions to problems using an iterative process involving the probabilistic selection of the fittest solutions and their variation by means of a set of genetic operators, usually crossover and mutation. GP has been successfully applied to a number of challenging real-world problem domains. Its operations and behaviour are now reasonably well understood thanks to a variety of powerful theoretical results. In this chapter, the main definitions and features of GP are introduced and its typical operations are described. Some of its applications are then surveyed. Some important theoretical results in this field, including some very recent ones, are reviewed and some of the most challenging open issues and directions for future research are discussed.",
• notes = "The Mechanics of Tree-Based GP, Examples of Real-World Applications of GP, GP Theory, Open Issues",
• size = "31 pages",

}

Genetic Programming entries for Leonardo Vanneschi Riccardo Poli

Citations