Transplant Evolution for Optimization of General Controllers

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InCollection{Weisser:2010:ntt,
  author =       "Roman Weisser and Pavel Osmera and Jan Roupec and 
                 Radomil Matousek",
  title =        "Transplant Evolution for Optimization of General
                 Controllers",
  booktitle =    "New Trends in Technologies: Control, Management,
                 Computational Intelligence and Network Systems",
  publisher =    "InTech",
  year =         "2010",
  editor =       "Er Meng Joo",
  chapter =      "5",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution, differential evolution, transplant
                 evolution",
  isbn13 =       "978-953-307-213-5",
  DOI =          "doi:10.5772/10419",
  size =         "18 pages",
  abstract =     "The aim of this paper is to describe a new
                 optimisation method that can create control equations
                 of general regulators. For this type of optimization a
                 new method was created and we call it Two-Level
                 Transplant Evolution (TLTE). This method allowed us to
                 apply advanced methods of optimisation, for example
                 direct tree reducing of tree structure of control
                 equation. The reduction method was named Arithmetic
                 Tree Reducing (ART). For the optimisation of control
                 equations of general controllers it is suitable to
                 combine two evolutionary algorithms. The main goal in
                 the first level of TLTE is the optimisation of the
                 structure of general controllers. In the second level
                 of TLTE the concrete parameters are optimised and the
                 unknown abstract parameters in the structure of
                 equations are set. The method TLTE was created by the
                 combination of the Transplant Evolution method (TE) and
                 the Differential Evolution method (DE). The Transplant
                 Evolution (TE) optimises the structure of the solution
                 with...",
  notes =        "'grammatical rules are chosen randomly'. shortening
                 structural mutation, algebraic reducing tree ART

                 VUT in Bruno",
}

Genetic Programming entries for Roman Weisser Pavel Osmera Jan Roupec Radomil Matousek

Citations