Name
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. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.5555/3463952.3464238 | AAMAS |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yifeng Zeng | 1 | 0 | 2.03 |
| Zhangrui Yao | 2 | 0 | 0.34 |
| Yinghui Pan | 3 | 0 | 2.37 |
| Wanqing Chen | 4 | 0 | 0.34 |
| Junxin Zhou | 5 | 0 | 0.34 |
| Junhan Chen | 6 | 0 | 0.34 |
| Biyang Ma | 7 | 0 | 2.70 |
| Zhong Ming | 8 | 1377 | 106.41 |