DANLI: Deliberative Agent for Following Natural Language Instructions

Yichi Zhang, Jianing Yang, Jiayi Pan, Shane Storks, Nikhil Devraj, Ziqiao Ma, Keunwoo Yu, Yuwei Bao, Joyce Chai


Abstract
Recent years have seen an increasing amount of work on embodied AI agents that can perform tasks by following human language instructions. However, most of these agents are reactive, meaning that they simply learn and imitate behaviors encountered in the training data. These reactive agents are insufficient for long-horizon complex tasks. To address this limitation, we propose a neuro-symbolic deliberative agent that, while following language instructions, proactively applies reasoning and planning based on its neural and symbolic representations acquired from past experience (e.g., natural language and egocentric vision). We show that our deliberative agent achieves greater than 70% improvement over reactive baselines on the challenging TEACh benchmark. Moreover, the underlying reasoning and planning processes, together with our modular framework, offer impressive transparency and explainability to the behaviors of the agent. This enables an in-depth understanding of the agent’s capabilities, which shed light on challenges and opportunities for future embodied agents for instruction following. The code is available at https://github.com/sled-group/DANLI.
Anthology ID:
2022.emnlp-main.83
Volume:
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Month:
December
Year:
2022
Address:
Abu Dhabi, United Arab Emirates
Editors:
Yoav Goldberg, Zornitsa Kozareva, Yue Zhang
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1280–1298
Language:
URL:
https://aclanthology.org/2022.emnlp-main.83
DOI:
10.18653/v1/2022.emnlp-main.83
Bibkey:
Cite (ACL):
Yichi Zhang, Jianing Yang, Jiayi Pan, Shane Storks, Nikhil Devraj, Ziqiao Ma, Keunwoo Yu, Yuwei Bao, and Joyce Chai. 2022. DANLI: Deliberative Agent for Following Natural Language Instructions. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 1280–1298, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
Cite (Informal):
DANLI: Deliberative Agent for Following Natural Language Instructions (Zhang et al., EMNLP 2022)
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PDF:
https://preview.aclanthology.org/naacl24-info/2022.emnlp-main.83.pdf