ATPT: Automate Typhoon Contingency Plan Generation from Text

Yifeng Zeng; Zhangrui Yao; Yinghui Pan; Wanqing Chen; Junxin Zhou; Junhan Chen; Biyang Ma; Zhong Ming

doi:10.5555/3463952.3464238

ATPT: Automate Typhoon Contingency Plan Generation from Text

Yifeng Zeng, Zhangrui Yao, Yinghui Pan^*, Wanqing Chen, Junxin Zhou, Junhan Chen, Biyang Ma, Zhong Ming

^*Corresponding author for this work

Computer Information Sciences Department

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

23 Downloads (Pure)

Abstract

Artificial intelligence (AI) planning models play an important role in decision support systems for disaster management e.g. typhoon contingency plan development. However, constructing an AI planning model always requires significant amount of manual effort, which becomes a bottleneck to emergency response in a time-critical situation. In this demonstration, we present a framework of automating a domain model of planning domain definition language from natural language input through deep learning techniques. We implement this framework in a typhoon response system and demonstrate automatic generation of typhoon contingency plan from official typhoon plan documents.

Original language	English
Title of host publication	AAMAS '21
Subtitle of host publication	Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems
Editors	Ulle Endriss, Ann Nowé, Frank Dignum, Alessio Lomuscio
Publisher	International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages	1776-1778
Number of pages	3
ISBN (Electronic)	9781713832621
ISBN (Print)	9781450383073
DOIs	https://doi.org/10.5555/3463952.3464238
Publication status	Published - 3 May 2021
Event	AAMAS 2021: 20th International Conference on Autonomous Agents and Multiagent Systems - Virtual, Southampton, United Kingdom Duration: 3 May 2021 → 7 May 2021 https://aamas2021.soton.ac.uk/

Publication series

Name	Proceedings of AAMAS
Publisher	International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS
ISSN (Print)	2523-5699

Conference

Conference	AAMAS 2021
Country/Territory	United Kingdom
City	Southampton
Period	3/05/21 → 7/05/21
Internet address	https://aamas2021.soton.ac.uk/

Keywords

Planning Domain Definition Language
Natural Language Process
Typhoon Contingency Plan

Access to Document

10.5555/3463952.3464238

p1788Final published version, 3.72 MB

http://www.ifaamas.org/Proceedings/aamas2021/forms/contents.htm

Cite this

Zeng, Y., Yao, Z., Pan, Y., Chen, W., Zhou, J., Chen, J., Ma, B., & Ming, Z. (2021). ATPT: Automate Typhoon Contingency Plan Generation from Text. In U. Endriss, A. Nowé, F. Dignum, & A. Lomuscio (Eds.), AAMAS '21: Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems (pp. 1776-1778). (Proceedings of AAMAS). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). https://doi.org/10.5555/3463952.3464238

Zeng, Yifeng ; Yao, Zhangrui ; Pan, Yinghui et al. / ATPT: Automate Typhoon Contingency Plan Generation from Text. AAMAS '21: Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems. editor / Ulle Endriss ; Ann Nowé ; Frank Dignum ; Alessio Lomuscio. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2021. pp. 1776-1778 (Proceedings of AAMAS).

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title = "ATPT: Automate Typhoon Contingency Plan Generation from Text",

abstract = "Artificial intelligence (AI) planning models play an important role in decision support systems for disaster management e.g. typhoon contingency plan development. However, constructing an AI planning model always requires significant amount of manual effort, which becomes a bottleneck to emergency response in a time-critical situation. In this demonstration, we present a framework of automating a domain model of planning domain definition language from natural language input through deep learning techniques. We implement this framework in a typhoon response system and demonstrate automatic generation of typhoon contingency plan from official typhoon plan documents.",

keywords = "Planning Domain Definition Language, Natural Language Process, Typhoon Contingency Plan",

author = "Yifeng Zeng and Zhangrui Yao and Yinghui Pan and Wanqing Chen and Junxin Zhou and Junhan Chen and Biyang Ma and Zhong Ming",

year = "2021",

month = may,

day = "3",

doi = "10.5555/3463952.3464238",

language = "English",

isbn = "9781450383073",

series = "Proceedings of AAMAS",

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editor = "Ulle Endriss and Ann Now{\'e} and Frank Dignum and Alessio Lomuscio",

booktitle = "AAMAS '21",

note = "AAMAS 2021 : 20th International Conference on Autonomous Agents and Multiagent Systems ; Conference date: 03-05-2021 Through 07-05-2021",

url = "https://aamas2021.soton.ac.uk/",

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Zeng, Y, Yao, Z, Pan, Y, Chen, W, Zhou, J, Chen, J, Ma, B & Ming, Z 2021, ATPT: Automate Typhoon Contingency Plan Generation from Text. in U Endriss, A Nowé, F Dignum & A Lomuscio (eds), AAMAS '21: Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems. Proceedings of AAMAS, International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), pp. 1776-1778, AAMAS 2021, Southampton, United Kingdom, 3/05/21. https://doi.org/10.5555/3463952.3464238

ATPT: Automate Typhoon Contingency Plan Generation from Text. / Zeng, Yifeng; Yao, Zhangrui; Pan, Yinghui et al.
AAMAS '21: Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems. ed. / Ulle Endriss; Ann Nowé; Frank Dignum; Alessio Lomuscio. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2021. p. 1776-1778 (Proceedings of AAMAS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Zeng, Yifeng

AU - Yao, Zhangrui

AU - Pan, Yinghui

AU - Chen, Wanqing

AU - Zhou, Junxin

AU - Chen, Junhan

AU - Ma, Biyang

AU - Ming, Zhong

PY - 2021/5/3

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N2 - Artificial intelligence (AI) planning models play an important role in decision support systems for disaster management e.g. typhoon contingency plan development. However, constructing an AI planning model always requires significant amount of manual effort, which becomes a bottleneck to emergency response in a time-critical situation. In this demonstration, we present a framework of automating a domain model of planning domain definition language from natural language input through deep learning techniques. We implement this framework in a typhoon response system and demonstrate automatic generation of typhoon contingency plan from official typhoon plan documents.

AB - Artificial intelligence (AI) planning models play an important role in decision support systems for disaster management e.g. typhoon contingency plan development. However, constructing an AI planning model always requires significant amount of manual effort, which becomes a bottleneck to emergency response in a time-critical situation. In this demonstration, we present a framework of automating a domain model of planning domain definition language from natural language input through deep learning techniques. We implement this framework in a typhoon response system and demonstrate automatic generation of typhoon contingency plan from official typhoon plan documents.

KW - Planning Domain Definition Language

KW - Natural Language Process

KW - Typhoon Contingency Plan

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SP - 1776

EP - 1778

BT - AAMAS '21

A2 - Endriss, Ulle

A2 - Nowé, Ann

A2 - Dignum, Frank

A2 - Lomuscio, Alessio

PB - International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)

T2 - AAMAS 2021

Y2 - 3 May 2021 through 7 May 2021

ER -

Zeng Y, Yao Z, Pan Y, Chen W, Zhou J, Chen J et al. ATPT: Automate Typhoon Contingency Plan Generation from Text. In Endriss U, Nowé A, Dignum F, Lomuscio A, editors, AAMAS '21: Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). 2021. p. 1776-1778. (Proceedings of AAMAS). doi: 10.5555/3463952.3464238

ATPT: Automate Typhoon Contingency Plan Generation from Text

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