Tackling the Abstraction and Reasoning Corpus (ARC) with Object-centric Models and the MDL Principle

• URL: http://arxiv.org/abs/2311.00545v1
• Date: Wed, 1 Nov 2023 14:25:51 GMT
• Title: Tackling the Abstraction and Reasoning Corpus (ARC) with Object-centric Models and the MDL Principle
• Authors: S\'ebastien Ferr\'e
• Abstract summary: We introduce object-centric models that are in line with the natural programs produced by humans. Our models can not only perform predictions, but also provide joint descriptions for input/output pairs. A diverse range of tasks are solved, and the learned models are similar to the natural programs.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The Abstraction and Reasoning Corpus (ARC) is a challenging benchmark, introduced to foster AI research towards human-level intelligence. It is a collection of unique tasks about generating colored grids, specified by a few examples only. In contrast to the transformation-based programs of existing work, we introduce object-centric models that are in line with the natural programs produced by humans. Our models can not only perform predictions, but also provide joint descriptions for input/output pairs. The Minimum Description Length (MDL) principle is used to efficiently search the large model space. A diverse range of tasks are solved, and the learned models are similar to the natural programs. We demonstrate the generality of our approach by applying it to a different domain.

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