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| Content Provider | IET Digital Library |
|---|---|
| Author | Zhou, Chao Wang, Hongwei Zhuo, Hankz Hankui |
| Abstract | This study investigates the emergency decision-making problem in a multi-agent system. Departments are modeled as agents to perform coordinated planning to obtain a global action plan with a short execution time constrained by a prescribed deadline. A novel multi-agent planning approach is proposed to coordinate for the solution among agents in the system. The approach consists of two stages. For the first stage, a coordinated planning and scheduling method is designed to generate a candidate global action plan. In this plan, durative actions are assigned to proper time intervals with the consideration of temporal relationships among agents. For the second stage, a coordination mechanism based on local heuristics is proposed to reduce the global time cost of the candidate plan to satisfy the deadline. An experimental study of emergency evacuation problem is conducted to demonstrate the effectiveness and efficiency of the proposed approach. |
| Starting Page | 447 |
| Ending Page | 455 |
| Page Count | 9 |
| ISSN | 17518644 |
| Volume Number | 9 |
| e-ISSN | 17518652 |
| Issue Number | Issue 3, Feb (2015) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-cta/9/3 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-cta.2014.0484 |
| Journal | IET Control Theory & Applications |
| Publisher Date | 2014-10-15 |
| Access Restriction | Open |
| Rights Holder | © The Institution of Engineering and Technology |
| Subject Keyword | Candidate Global Action Plan Deadline Required Emergency Response Tasks Decision Making Durative Actions Emergency Decision-making Problem Emergency Evacuation Problem Emergency Management Local Heuristics Multi-agent System Multiagent Coordinated Planning Approach Multiagent System Planning Scheduling Scheduling Method Short Execution Time Time Intervals |
| Content Type | Text |
| Resource Type | Article |
| Subject | Control and Optimization Control and Systems Engineering Human-Computer Interaction Electrical and Electronic Engineering Computer Science Applications |
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