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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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 languageEnglish
Title of host publicationAAMAS '21
Subtitle of host publicationProceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems
EditorsUlle Endriss, Ann Nowé, Frank Dignum, Alessio Lomuscio
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1788-1790
Number of pages3
ISBN (Print)9781450383073
DOIs
Publication statusPublished - 3 May 2021
EventAAMAS 2021: 20th International Conference on Autonomous Agents and Multiagent Systems - Virtual, Southampton, United Kingdom
Duration: 3 May 20217 May 2021
https://aamas2021.soton.ac.uk/

Publication series

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

Conference

ConferenceAAMAS 2021
CountryUnited Kingdom
CitySouthampton
Period3/05/217/05/21
Internet address

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