%0 Journal Article
%T Path Selection in Disaster Response Management Based on Q-learning<br>
%A Zhao-Pin Su
%A Jian-Guo Jiang
%A Chang-Yong Liang
%A Guo-Fu Zhang
%A <br>
%J 国际自动化与计算杂志
%D 2011
%I 
%X Suitable rescue path selection is very important to rescue lives and reduce the loss of disasters, and has been a key issue in the field of disaster response management. In this paper, we present a path selection algorithm based on Q-learning for disaster response applications. We assume that a rescue team is an agent, which is operating in a dynamic and dangerous environment and needs to find a safe and short path in the least time. We first propose a path selection model for disaster response management, and deduce that path selection based on our model is a Markov decision process. Then, we introduce Q-learning and design strategies for action selection and to avoid cyclic path. Finally, experimental results show that our algorithm can find a safe and short path in the dynamic and dangerous environment, which can provide a specific and significant reference for practical management in disaster response applications.
%K Disaster response management
%K path selection
%K agent
%K self-organizing
%K Markov decision process
%K Q-learning<br>
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7139AD613512F4F05F6D525B914296AA&aid=B1E3C3908561D64D8501F4D469C15A37&yid=9377ED8094509821&vid=5D311CA918CA9A03&iid=CA4FD0336C81A37A&sid=8C83C265AD318E34&eid=F24949CFDB502409&journal_id=1476-8186&journal_name=国际自动化与计算杂志&referenced_num=0&reference_num=27