A genetic programming based rule generation approach for intelligent control systems

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Chiang:2010:3CA,
  author =       "Cheng-Hsiung Chiang",
  title =        "A genetic programming based rule generation approach
                 for intelligent control systems",
  booktitle =    "2010 International Symposium on Computer Communication
                 Control and Automation (3CA)",
  year =         "2010",
  month =        may,
  volume =       "1",
  pages =        "104--107",
  abstract =     "This paper presents an intelligent control system
                 (namely GPICS). The GPICS consists of a Symbolic Rule
                 Controller, a Percepter and a rAdaptor. The Percepter
                 judges whether the control system can adapt the
                 environment. If the system is inadaptable, the rAdaptor
                 will be activated to search the new rule to adapt the
                 environment; otherwise, the controller will keeps on
                 its controlling assignments. Once the rAdaptor is
                 activated, the flexible genetic programming will be
                 employed for searching the new rule. Simulation results
                 of the robotic path planning showed that the GPICS
                 method can successfully find a satisfactory path.",
  keywords =     "genetic algorithms, genetic programming, genetic
                 programming intelligent control system, percepter,
                 radaptor, rule generation approach, symbolic rule
                 controller, intelligent control, learning (artificial
                 intelligence), path planning",
  DOI =          "doi:10.1109/3CA.2010.5533882",
  notes =        "Also known as \cite{5533882}",
}

Genetic Programming entries for Cheng-Hsiung Chiang

Citations