- author = "Justinian P. Rosca and Dana H. Ballard",
- title = "Rooted-Tree Schemata in Genetic Programming",
- booktitle = "Advances in Genetic Programming 3",
- publisher = "MIT Press",
- year = "1999",
- editor = "Lee Spector and William B. Langdon and Una-May O'Reilly and Peter J. Angeline",
- chapter = "11",
- pages = "243--271",
- address = "Cambridge, MA, USA",
- month = jun,
- keywords = "genetic algorithms, genetic programming",
- ISBN = "0-262-19423-6",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/aigp3/ch11.pdf",
-
DOI = "
doi:10.7551/mitpress/1110.003.0015",
-
abstract = "we present a novel way of addressing the issue of
variable complexity of evolved solutions and a revised
interpretation of how Genetic Programming (GP)
constructs solutions, based on the rooted-tree schema
concept.
A rooted-tree schema is a simple relation on the space of tree-shaped structures which provides a quantifiable partitioning of the search space. Formal manipulation of rooted-tree schemata allows: (1) The role of the size in the selection and survival of evolved expressions to be made explicit; (2) The interrelationship between parsimony penalty, size, and fitness of evolved expressions to be clarified and better understood; (3) The introduction of alternative approaches to evolving parsimonious solutions by preventing rooted-tree schema from bloating.
The rooted-tree schema concept provides a top-down perspective of how program expressions are evolved, contrary to the common belief that small pieces of code, or building blocks, are gradually assembled to create solutions. Analysis shows that GP, while it improves solutions, combines both bottom-up and top-down refinement strategies.",
- notes = "AiGP3 See http://cognet.mit.edu",
