- author = "Ting Hu and Lukas Sekanina",
- title = "{EuroGP} 2019 Panel Discussion: What is the Killer Application of {GP}?",
- journal = "SIGEVOlution newsletter of the ACM Special Interest Group on Genetic and Evolutionary Computation",
- year = "2019",
- volume = "12",
- number = "2",
- pages = "3--7",
- month = aug,
- keywords = "genetic algorithms, genetic programming, robotics, SBSE, APR, SapFix",
- ISSN = "1931-8499",
-
URL = "
https://evolution.sigevo.org/issues/SIGEVOlution1202.pdf",
-
DOI = "
doi:10.1145/3357514.3357515",
- acmid = "3357515",
- size = "4.3 pages",
-
abstract = "Moderator: Ting Hu, Memorial University,
Canada
Panelists: Gusz Eiben, Vrije Universiteit Amsterdam, the Netherlands Given the fact that evolution can produce intelligence, it is plausible that Artificial Evolution can produce Artificial Intelligence.
Gabriela Ochoa, University of Stirling, Scotland GP has already proved to be a powerful problem-solving and design tool in many domains, so there are already several killer-applications that are part of our everyday lives! CGP \cite{Lones:2017:JMS}
James Foster, University of Idaho, USA GP is much more likely to be used under the hood. I teach computers to program themselves.
Risto Miikkulainen, University of Texas at Austin and Cognizant, USA GP/EC is a creative approach to AI.",
