Evolving driving controllers using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Ebner:2009:CIG,

• author = "Marc Ebner and Thorsten Tiede",
• title = "Evolving driving controllers using Genetic Programming",
• booktitle = "IEEE Symposium on Computational Intelligence and Games, CIG 2009",
• year = "2009",
• pages = "279--286",
• address = "Milan, Italy",
• month = "7-10 " # sep,
• 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",
• isbn13 = "978-1-4244-4814-2",
• URL = "https://stubber.math-inf.uni-greifswald.de/~ebner/resources/uniTu2/evoCarDriver.pdf",
• DOI = "doi:10.1109/CIG.2009.5286465",
• size = "8 pages",
• 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.",
• notes = "Also known as \cite{5286465}",

}

Genetic Programming entries for Marc Ebner Thorsten Tiede

Citations