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This is a Experimental Study study.

October 13, 2025Open Access

NeSyC: A Neuro-symbolic Continual Learner For Complex Embodied Tasks In Open Domains

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NeSyC enhances embodied agents' performance on complex tasks, employing neuro-symbolic methods and LLMs.

NeSyC demonstrates superior efficiency in executing complex tasks within open-domain environments.
Experiments reveal NeSyC's effectiveness across multiple benchmarks, including Minecraft and RLBench.
The framework translates limited experiences into actionable knowledge through a novel contrastive validation scheme.
Incorporating memory-based monitoring enhances error detection and promotes knowledge refinement across domains.

Choi et al. (2025) studied this question.

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