Information extraction in emergency management missions: an adaptive multi-agent approach

IF 0.1 Q4 MANAGEMENT
A. C. Calderon, P. Johnson
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引用次数: 1

Abstract

With increasing demands for autonomous agents to work alongside humans in emergency management response (EMR), considerations of translations of human to machine language (and the converse) are timely. We present a prototype where the translation is dealt with by restricting communications to occur through a form of controlled natural language (CNL) (Fuchs and Schwitter, 1995). The prototype is new in that it allows for communications between both physical and virtual autonomous agents, agents are assigned different levels of autonomy, and it includes a level of information hiding that allows for information to be passed to relevant agents, whilst keeping those (humans) involved anonymous. A real-life mission is then used to exemplify how information is retrieved and communicated in the prototype. Finally, some usability experimental results are presented.
应急管理任务中的信息提取:自适应多智能体方法
随着对自主代理在应急管理响应(EMR)中与人类一起工作的需求不断增加,考虑将人类语言翻译为机器语言(反之亦然)是及时的。我们提出了一个原型,在这个原型中,翻译是通过一种受控自然语言(CNL)的形式来限制通信的发生(Fuchs和Schwitter, 1995)。该原型的新颖之处在于它允许物理和虚拟自治代理之间的通信,代理被分配不同的自治级别,并且它包括一个级别的信息隐藏,允许将信息传递给相关代理,同时保持那些(人类)参与匿名。然后使用现实生活中的任务来举例说明如何在原型中检索和交流信息。最后给出了一些可用性实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
0.80
自引率
0.00%
发文量
18
期刊介绍: The IJEM is a refereed international journal published to address contingencies and emergencies as well as crisis and disaster management. Coverage includes the issues associated with: storms and flooding; nuclear power accidents; ferry, air and rail accidents; computer viruses; earthquakes etc.
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