| Bibtype | Inproceedings |
|---|---|
| Bibkey | Fischer/etal/2020a |
| Author | Fischer, Raphael and Jakobs, Matthias and Mücke, Sascha and Morik, Katharina |
| Ls8autor |
Fischer, Raphael
Jakobs, Matthias Morik, Katharina Mücke, Sascha |
| Editor | Trabold, Daniel and Welke, Pascal and Piatkowski, Nico |
| Title | Solving Abstract Reasoning Tasks with Grammatical Evolution |
| Booktitle | Proceedings of the {LWDA} 2020 Workshops: {KDML}, {FGWM}, {FGWI-BIA}, and {FGDB} |
| Series | {CEUR} Workshop Proceedings |
| Pages | 6--10 |
| 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 offthe-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 4% out of 900 participants. |
| Month | 09 |
| Year | 2020 |
| Projekt | ML2R |
| Url | https://www.ifd2020.nrw/wp-content/uploads/2020/09/LWDA2020_Proceedings.pdf |
|---|