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New Symbolic Solver Tackles Abstraction and Reasoning Corpus with Evolutionary Computation

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a novel symbolic solver for the Abstraction and Reasoning Corpus (ARC) using evolutionary computation. This approach, submitted to the ARC-AGI-2 main contest, uniquely evolves the grid parser and output projector alongside the program itself, allowing a task-specific language to emerge. It also incorporates object-aware fitness evaluation to better grade partially correct outputs beyond simple pixel discrepancies. AI

IMPACT Introduces a new evolutionary computation method for symbolic AI, potentially advancing generalization capabilities in AI systems.

RANK_REASON This is a research paper detailing a novel approach to a benchmark. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New Symbolic Solver Tackles Abstraction and Reasoning Corpus with Evolutionary Computation

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This is a research paper detailing a novel approach to a benchmark. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Luca Favole, Giorgio Mongardi, Giovanni Squillero, Alberto Tonda ·

    Ceci n'est pas une pipe -- Toward a Symbolic Solver for the Abstraction and Reasoning Corpus Using Evolutionary Computation

    arXiv:2611.13831v1 Announce Type: new Abstract: The Abstraction and Reasoning Corpus (ARC) is a benchmark designed to assess the capability of Artificial Intelligence (AI) systems to generalize starting from a few samples, a task humans excel at. The ARC-AGI contests held since 2…

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