Evolving driving controllers using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4202

  author =       "Marc Ebner and Thorsten Tiede",
  title =        "Evolving driving controllers using Genetic
  booktitle =    "IEEE Symposium on Computational Intelligence and
                 Games, CIG 2009",
  year =         "2009",
  month =        sep,
  pages =        "279--286",
  keywords =     "genetic algorithms, genetic programming, computational
                 gaming, computational learning approaches, computer
                 gaming, driving controllers, manually crafted race car
                 driver, virtual drivers, computer games, control
                 engineering computing, driver information systems,
                 learning (artificial intelligence), virtual reality",
  abstract =     "Computational gaming requires the automatic generation
                 of virtual opponents for different game levels. We have
                 turned to artificial evolution to automatically
                 generate such game players. In particular, we have used
                 genetic programming to automatically evolve computer
                 programs for computer gaming. With genetic programming,
                 in theory, it is possible to generate any kind of
                 program. The programs are not constrained as much as
                 they are in other computational learning approaches,
                 e.g. neural networks. We show how genetic programming
                 improved upon a manually crafted race car driver
                 (proportional controller). The open race car simulator
                 TORCS was used to evaluate the virtual drivers.",
  DOI =          "doi:10.1109/CIG.2009.5286465",
  notes =        "Also known as \cite{5286465}",

Genetic Programming entries for Marc Ebner Thorsten Tiede