- author = "Hitoshi Iba and Hugo {de Garis} and Taisuke Sato",
- title = "Genetic Programming with Local Hill-Climbing",
- booktitle = "Parallel Problem Solving from Nature III",
- year = "1994",
- editor = "Yuval Davidor and Hans-Paul Schwefel and Reinhard M{\"a}nner",
- series = "LNCS",
- volume = "866",
- pages = "334--343",
- address = "Jerusalem",
- publisher_address = "Berlin, Germany",
- month = "9-14 " # oct,
- publisher = "Springer-Verlag",
- keywords = "genetic algorithms, genetic programming",
- ISBN = "3-540-58484-6",
-
URL = "
https://rdcu.be/diflR",
-
URL = "http://www.springer.de/cgi-bin/search_book.pl?isbn=3-540-58484-6",
-
DOI = "
10.1007/3-540-58484-6_274",
- size = "10 pages",
- abstract = "This paper proposes a new approach to Genetic Programming (GP). In traditional GP, recombination can cause frequent disruption of building-blocks or mutation can cause abrupt changes in the semantics. To overcome these difficulties, we supplement traditional GP with a recovery mechanism of disrupted building-blocks. More precisely, we integrate the structural search of traditional GP with a local hill-climbing search, using a relabeling procedure. This integration allows us to extend GP for Boolean and numerical problems. We demonstrate the superior effectiveness of our approach with experiments in Boolean concept formation and symbolic regression.",
-
notes = "'We demonstrate the superior effectiveness of GP+local
Hill Climbing with experiments in Boolean concept
formation and symbolic regression'. Boolean GP combines
GP with Adaptive Logic Network trees. Combination can
evove to cope with time varying fitness functions.
Numerical GP combines GP with GMDH (Group Method of
Data Handling, Ivakhnenko)
PPSN3 see also technical note \cite{Iba:1994:GPlHC}",
