Unsupervised Learning of Neuro-symbolic Rules for Generalizable Context-aware Planning in Object Arrangement Tasks-Reference-Cited by-同舟云学术

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Unsupervised Learning of Neuro-symbolic Rules for Generalizable Context-aware Planning in Object Arrangement Tasks

Published:2024-05-13 Issue: Volume:34 Page:12865-12872
ISSN:
Container-title:2024 IEEE International Conference on Robotics and Automation (ICRA)
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Author:

Sharma Siddhant¹,Tuli Shreshth¹,Paul Rohan²

Affiliation:

1. IIT Delhi

2. IIT Delhi,Computer Science and Engg. (CSE) and Yardi School of AI (ScAI)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10609961/10609862/10610696.pdf?arnumber=10610696

Reference31 articles.

1. Neural production systems;Goyal;Advances in Neural Information Processing Systems,2021

2. Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor;Haarnoja

3. Truly proximal policy optimization;Wang

4. Nltopddl: One-shot learning of pddl models from natural language process manuals;Miglani

5. HDDL: An Extension to PDDL for Expressing Hierarchical Planning Problems

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