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 heterogeneous semantics 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.