Cartesian Ant Programming with node release mechanism

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  author =       "Jun-ichi Kushida and Akira Hara and 
                 Tetsuyuki Takahama",
  booktitle =    "8th IEEE International Workshop on Computational
                 Intelligence and Applications (IWCIA)",
  title =        "Cartesian Ant Programming with node release
  year =         "2015",
  pages =        "83--88",
  URL =          "",
  keywords =     "genetic algorithms, genetic programming, Ant colony
                 optimisation, Artificial neural networks, Dynamic
                 scheduling, Programming, Resource management, Ant
                 Colony Optimisation, Cartesian Ant Programming",
  DOI =          "doi:10.1109/IWCIA.2015.7449467",
  ISSN =         "1883-3977",
  month =        nov,
  abstract =     "Genetic Programming (GP) is one of the evolutionary
                 algorithm that automatically creates a computer
                 program. Cartesian GP (CGP) is one of the extensions of
                 GP, which generates the graph structural programs. By
                 using the graph structure, the solutions can be
                 represented by more compact programs. Therefore, CGP is
                 widely applied to the various problems. As a different
                 approach from the evolutionary algorithm, there is the
                 Ant Colony Optimisation (ACO), which is an optimisation
                 method for combinatorial optimisation problems based on
                 the cooperative behaviour of ants. By using pheromone
                 communication, the promising solution space can be
                 searched intensively. A number of ACO variants have
                 been proposed for the various problem domains. One of
                 them, ACO to automatic programming has been proposed
                 recently. This new model, called Cartesian Ant
                 Programming (CAP), is based graph representations in
                 CGP with search mechanism of ACO. The connections of
                 nodes are optimised by ant-based search instead of
                 genetic operators. However, it is difficult to use the
                 most part of given nodes as an effective node which are
                 contained in the created program. In this paper, we
                 propose a node release mechanism for CAP in order to
                 use given nodes more efficiently. In the mechanism,
                 specific nodes are set to unavailable at the start of
                 the run. After certain step, unavailable nodes are
                 released and all nodes become available. We compared
                 the search performance of CAP with node release
                 mechanism and normal CAP, and showed the effectiveness
                 of our method.",
  notes =        "Also known as \cite{7449467}",

Genetic Programming entries for Jun-ichi Kushida Akira Hara Tetsuyuki Takahama