摘要翻译：
我们对在不确定和部分感知环境中的风险检测和应急响应的多智能体系统开发问题感兴趣。在多智能体系统中，对当前状况的评估经历了三个阶段。第一次，情况是以动态的方式表现出来的。第二步，对该情景进行特征描述，最后，将其与其他已知的类似情景进行比较。在本文中，我们提出了一个被观测环境的信息模型，并应用于RoboCupRescue仿真系统中。来自环境的信息根据分类法并使用语义特征进行格式化。后者是由一个良好的领域本体定义的，并由旨在动态表示当前情况的事实代理管理。
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英文标题：
《Agent-Based Perception of an Environment in an Emergency Situation》
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作者：
Fahem Kebair (LITIS), Fr\'ed\'eric Serin (LITIS), Cyrille Bertelle
  (LITIS)
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最新提交年份：
2008
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  We are interested in the problem of multiagent systems development for risk detecting and emergency response in an uncertain and partially perceived environment. The evaluation of the current situation passes by three stages inside the multiagent system. In a first time, the situation is represented in a dynamic way. The second step, consists to characterise the situation and finally, it is compared with other similar known situations. In this paper, we present an information modelling of an observed environment, that we have applied on the RoboCupRescue Simulation System. Information coming from the environment are formatted according to a taxonomy and using semantic features. The latter are defined thanks to a fine ontology of the domain and are managed by factual agents that aim to represent dynamically the current situation.
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PDF链接：
https://arxiv.org/pdf/0804.0558