- author = "Hitoshi Iba",
- title = "Random Tree Generation for Genetic Programming",
- booktitle = "Parallel Problem Solving from Nature IV, Proceedings of the International Conference on Evolutionary Computation",
- year = "1996",
- editor = "Hans-Michael Voigt and Werner Ebeling and Ingo Rechenberg and Hans-Paul Schwefel",
- series = "LNCS",
- volume = "1141",
- pages = "144--153",
- address = "Berlin, Germany",
- publisher_address = "Heidelberg, Germany",
- month = "22-26 " # sep,
- publisher = "Springer Verlag",
- keywords = "genetic algorithms, genetic programming",
- ISBN = "3-540-61723-X",
-
DOI = "
doi:10.1007/3-540-61723-X_978",
- size = "10 pages",
- abstract = "This paper introduces a random tree generation algorithm for GP (Genetic Programming). Generating random trees is an essential part of GP. However, the recursive method commonly used in GP does not necessarily generate random trees, i.e the standard GP initialisation procedure does not sample the space of possible initial trees uniformly. This paper proposes a truly random tree generation procedure for GP. Our approach is grounded upon a bijection method, i.e., a 1-1 correspondence between a tree with n nodes and some simple word composed by letters x and y. We show how to use this correspondence to generate a GP tree and how GP search is improved by using this randomness",
-
notes = "
bijection, tree_by_dyck
Demonstrated on Mackey-Glass compared to 'grow' method (not ramped half-and-half)",
- affiliation = "Electrotechnical Laboratory (ETL) Machine Inference Section 1-1-4 Umezono, Tsukuba Science City 305 Ibaraki Japan 1-1-4 Umezono, Tsukuba Science City 305 Ibaraki Japan",
