# LG AI Research — [AAAI 2022] Learning Parameterized Task Structure for Generalization to Unseen Entities

- Company: LG AI Research (lgresearch.ai)
- Announced: 2022-07-27
- Category: research-paper
- Coverage: not counted
- Announcement: yes
- Group: announcements
- Source: https://www.lgresearch.ai/blog/view?seq=235
- Record: https://forck.live/items/4938-aaai-2022-learning-parameterized-task-structure-for-generalization-to-unseen
- Subject: EXAONE

LG AI Research introduces Parameterized Subtask Graph Inference (PSGI), a method for inferring hierarchical and compositional task structures in a first-order logic manner, enabling generalization to unseen entities. The method is tested on cooking, mining, and simulated domains, showing improved efficiency and generalizability over prior work.

## Evidence

Verbatim from https://www.lgresearch.ai/blog/view?seq=235:

> We introduce Parameterized Subtask Graph Inference (PSGI), which infers the structure of hierarchical and compositional tasks in a first order logic manner.

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Record: https://forck.live/items/4938-aaai-2022-learning-parameterized-task-structure-for-generalization-to-unseen
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