多智能体城市交通仿真。第二部分：处理 非凡

是 否 +2 论坛币

k人 参与回答

经管之家送您一份

应届毕业生专属福利!

求职就业群

赵安豆老师微信：zhaoandou666

经管之家联合CDA

送您一个全额奖学金名额~ !

立即领取

感谢您参与论坛问题回答

经管之家送您两个论坛币！

+2 论坛币

摘要翻译：
在概率风险管理中，风险由两个量来表征：给定活动或行动可能导致的不利后果的大小（或严重程度），以及给定不利后果发生的可能性。但是，一种风险很少孤立地存在：必须研究一连串的后果，因为一种风险的结果可能会增加其他风险的可能性。系统理论必须对经典PRM进行补充。事实上，这些链是由许多不同的元素组成的，所有这些元素都可能在许多不同的层面上具有至关重要的重要性。此外，当设想城市灾难时，空间和时间限制是这些灾难链的运作和动态的关键决定因素：模型必须包括所研究风险的正确空间拓扑。最后，文献强调了小事件对更大范围风险的重要性：城市风险管理模型属于自组织临界理论。我们选择multiagent系统将这一特性纳入我们的模型：一个agent的行为可以改变其中重要群体的动态。
---
英文标题：
《A multiagent urban traffic simulation. Part II: dealing with the
  extraordinary》
---
作者：
Eric Daud\'e (IDEES), Pierrick Tranouez (LITIS), Patrice Langlois
  (IDEES)
---
最新提交年份：
2009
---
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。
--

---
英文摘要：
  In Probabilistic Risk Management, risk is characterized by two quantities: the magnitude (or severity) of the adverse consequences that can potentially result from the given activity or action, and by the likelihood of occurrence of the given adverse consequences. But a risk seldom exists in isolation: chain of consequences must be examined, as the outcome of one risk can increase the likelihood of other risks. Systemic theory must complement classic PRM. Indeed these chains are composed of many different elements, all of which may have a critical importance at many different levels. Furthermore, when urban catastrophes are envisioned, space and time constraints are key determinants of the workings and dynamics of these chains of catastrophes: models must include a correct spatial topology of the studied risk. Finally, literature insists on the importance small events can have on the risk on a greater scale: urban risks management models belong to self-organized criticality theory. We chose multiagent systems to incorporate this property in our model: the behavior of an agent can transform the dynamics of important groups of them.
---
PDF链接：
https://arxiv.org/pdf/0910.1026

扫码加我 拉你入群

请注明：姓名-公司-职位

以便审核进群资格，未注明则拒绝

分享0 收藏0 回帖

关键词：城市交通 智能体 Consequences Determinants Presentation 风险管理 研究 属于 PRM 因素