- author = "Raphael Fischer and Matthias Jakobs and Sascha Muecke and Katharina Morik",
- title = "Solving Abstract Reasoning Tasks with Grammatical Evolution",
- booktitle = "Proceedings of the Conference Lernen, Wissen, Daten, Analysen, LWDA 2020",
- year = "2020",
- editor = "Daniel Trabold and Pascal Welke and Nico Piatkowski",
- volume = "2738",
- series = "CEUR Workshop Proceedings",
- pages = "6--10",
- address = "Online",
- month = sep # " 9-11",
- publisher = "CEUR-WS.org",
- note = "KDML Workshop",
- keywords = "genetic algorithms, genetic programming, grammatical evolution, machine learning, reasoning",
- ISSN = "1613-0073",
- bibdate = "2020-11-16",
- bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/lwa/lwda2020.html#FischerJMM20",
-
URL = "
http://ceur-ws.org/Vol-2738",
-
URL = "
http://ceur-ws.org/Vol-2738/LWDA2020_paper_8.pdf",
- size = "5 pages",
- abstract = "The Abstraction and Reasoning Corpus (ARC) comprising image-based logical reasoning tasks is intended to serve as a benchmark for measuring intelligence. Solving these tasks is very difficult for off-the-shelf ML methods due to their diversity and low amount of training data. We here present our approach, which solves tasks via grammatical evolution on a domain-specific language for image transformations. With this approach, we successfully participated in an online challenge, scoring among the top 4percent out of 900 participants.",
-
notes = "urn:nbn:de:0074-2738-5
TU Dortmund, AI Group, Dortmund, Germany",
