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基于agent的仿真系统建模 被引量:18

Modeling of agent-based simulation system
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摘要 建模是人类认识世界和改造世界的主要方法之一.常用的数学模型有物理模型,数学模型,图示模型等等.从人工智能领域中发展起来的agent技术,为仿真系统的建模提供了新的方法和思路.本论文提出了面向a-gent的仿真系统建模方法,以城市交通流的微观仿真系统为例讨论了系统的建模过程,并编程实现了系统原型. Modeling is one of the main methods used to research our world. Different kinds of models can be settled to solve different problems, such as physical models, mathematical models, figural models etc. The agent technology, which is developed from the artificial intelligence, provides the simulation of complex systems with new methodology and idea. In this paper, an agent-programming and an agent- oriented modeling method of simulation system are introduced. Also, as an example, the modeling process of the urban traffic flow microscopic simulation system is discussed and a prototype is developed.
作者 李英 马寿峰
出处 《系统工程学报》 CSCD 北大核心 2006年第3期225-231,共7页 Journal of Systems Engineering
基金 国家自然科学基金资助项目(70001003) 天津市自然科学基金资助项目(023607311)
关键词 AGENT 仿真 建模 agent simulation modeling
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参考文献10

  • 1李建华,王兆青,诸鸿文,顾尚杰.按需仿真系统仿真建模及并行实现框架[J].上海交通大学学报,1999,33(1):88-91. 被引量:4
  • 2Michael W.多agent系统引论[M].北京:电子工业出版社,2003.63—69.
  • 3孙晋文,李明树,鄂卓茂.基于Agent的智能交通体系及仿真[J].计算机仿真,2002,19(3):46-49. 被引量:19
  • 4孙晋文,李明树,鄂卓茂.智能交通仿真与车辆Agent决策策略的研究[J].计算机工程与应用,2002,38(8):246-247. 被引量:4
  • 5Ehlert P A M, Rothkrantz L J M. Microscopic traffic simulation with reactive driving agents[A]. In: Proceedings of the 2001 IEEE Intelligent Transportation Systems Conference[C]. Oakland: IEEE, 860-865.
  • 6Roozemond D A. Using intelligent agents for pro-active, real-time urban intersection control[J]. European Journal of Operational Research, 2001, 131(2): 293-301.
  • 7Ossowski S, Jose C, Ana G S. A case of muhiagent decision support: Using autonomous agents for urban traffic control[A]. In: Progress in Artificial Intelligence-IBERAMIA'98[C]. Berlin: Springer, 1998. 100-111.
  • 8Lenzmann B, Wachsmuth I. Contract-net-based learning in a user-adaptive interface agency[ A]. In: Distributed Artificial Intelligence Meets Machine Learning[ C]. Berlin: Springer, 1997. 202-222.
  • 9Gu P, Maddox A B. A framework for distributed reinforcement learning[ A]. In: Adaption and Learning in Multi-Agent Systems [C]. Berlin: Springer, 1995. 97-112.
  • 10Bazan A L C. Traffic signal coordination based on distributed problem solving[A]. In:7th IFAC/IFORS Symposium on Transportation Systems: Theory and Application of Advanced Technology[ C]. Tianjin: 1994, 3: 957-962.

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