复杂系统基于Agent的建模与仿真方法研究及应用
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
复杂系统与复杂性科学是21世纪的科学,其研究方法是近代以来科学方法论的又一场革命,将为人们提供全新的了解自然界奥秘的手段。当前,对于自然现象、社会、经济、政治、军事、管理、生物以及工程(特别是航天工程)等领域复杂系统与复杂性的研究,呼唤新的建模与仿真方法的出现,基于Agent的建模与仿真(Agent-Based Modeling and Simulation, ABMS)方法应运而生。ABMS是当前建模与仿真领域的研究热点。论文以复杂系统与复杂性理论为立论基础与研究背景,以空间作战和卫星系统的建模与仿真为立题背景,开展ABMS方法学的相关问题研究,并将其应用到卫星系统的建模与仿真中,以期使ABMS方法学成为一套完善的建模与仿真理论,并能够指导具体复杂系统的建模与仿真研究。
     系统地阐述了复杂系统与复杂性理论的起源,结合前人的研究成果,分析和总结了复杂系统与复杂性有关的理论与方法,从本体论、认识论和方法论角度对复杂性进行了深刻的认识与理解,强调了建模与仿真在复杂系统研究中的重要地位。从复杂性理论出发,对空间信息系统的复杂性进行了分析和探讨,并提出了空间信息系统的研究思路。
     ABMS方法学是研究复杂系统的科学方法论。论文详细阐述了ABMS方法学的基本思想、特点和应用领域,提出了基于Agent的建模与仿真概念化框架,并因此界定了ABMS方法的研究内容。在此框架下,给出了ABMS方法学意义下包括Agent、消息、复杂系统以及基于Agent的仿真的形式化描述。讨论了基于Agent的模型校核与确认相关问题,探讨了基于Agent的模型有效性确认方法。建立了规范的ABMS的研究步骤,用来指导和规范复杂系统的建模与仿真,以减少建模与仿真的复杂度,提高模型的重用性与可用性。
     采用多种形式化方法对基于Agent的建模方法与模型描述进行了深入的研究,包括基于Agent的模型框架及基于Agent的行为建模两个方面。提出了一个包括实体、对象和Agent在内的三层抽象模型框架,并对相关的概念进行了形式化定义与描述,阐述了Agent模型实现相关的细节。对虚拟环境中Agent的行为建模问题进行了研究,对Agent的动作、行为以及约束等概念进行了定义与描述,提出并形式化描述了一种包含Agent的自主行为和交互行为的行为模型;为了实现复杂的智能行为以及行为的复用与集成,提出了一种包含行为聚合与分解、行为特化与泛化的行为抽象机制,并对该机制进行了形式化描述。在行为建模方法的基础上,对预警卫星的预警行为进行了分析,并对预警卫星的凝视相机的数据获取行为进行了建模。
     在ABMS概念化框架的支持下,提出了一种包含仿真基础服务模型和Agent仿真模型在内的基于Agent的建模与分布仿真软件框架,阐述了其中的关键功能组件及相关的时间算法。这种框架具有平台独立、开放性强,重用性强以及支持层次仿真、建模环境与仿真环境分离开来等特点。基于此框架,利用面向对象的思想,采用Java语言实现了一个基于Agent的分布仿真环境原型系——ADSimE,可保证领域专家以最简单、灵活的方式来进行复杂系统分布仿真。
The theories of complex systems and complexity are the sciences of 21st century, whose research method is another revolution for scientific methodology since modern times, and will provide people with new solutions to uncover the miracles of the nature. The researches needed for complex systems and complexity in natural phenomena, society, economy, polity, military, biology, management and engineering (especially aerospace engineering) impose a great challenge to the current theories and methods of modeling and simulation (M&S).While the novel Agent-Based Modeling and Simulation (ABMS) methodology, which is the hot topic today in M&S field, can fulfill the requirements. Based on the theories of complex systems and complexity, the paper has conducted research on ABMS methodology and problems relevant to the M&S of space operation and satellite systems, which are both complex systems. The purpose of the paper is to make ABMS become a perfect theory of M&S, which can instruct the research for complex systems.The provenance of complex systems and complexity was expatiated systematically. Moreover, the theories and methods for complex systems and complexity were also analyzed and summarized. From the views of ontology, epistemology and methodology the apprehension of complexity was also stated. In addition, the significance of M&S in the research of complex systems was emphasized and a research approach for complex systems was proposed. Based on the complexity theories, the complexities of space information system was analyzed and discussed.The ABMS is the uppermost and effective research methodology for complex systems. The basic thoughts, characteristics and application fields of ABMS were stated systematically. After that, a novel conceptual framework for ABMS was proposed creatively, which bounded the research contents of ABMS impliedly. The framework can be view as the evaluation framework for the ABMS system that has been existed. Thereafter, the agent, message, complex systems and agent-based simulation were defined and represented formally according to this framework. The methods of verification and validation for agent-based models were also discussed. What's more, the principles and steps, which should be followed by ABMS, were established.Agent-based modeling, including agent-based models framework and agent-based behavior modeling, were studied thoroughly by multi-formal methods. A 3-tier abstract models framework including entity, object and agent was proposed for agent-based modeling, and the concepts about entity, object, and agent were defined and represented by formal specifications. To model the behavior of agent in virtual environment, an agent-based behavior model including the autonomous behavior model and global interoperable behavior model was synthesized. In addition, the concepts relevant to behavior were defined formally. Based on the behavior model, the formal abstract mechanisms for synthetic and intelligent behavior including behavior aggregate and disaggregate; behavior specialization and generalization were analyzed. This gives the theoretical basis for
    realizing the reusability and synthetic of complex behavior. Based on the research of behavior modeling, the early warning behavior of early warning satellite was modeled.According to the requirement of ABMS methodology, an agent-based modeling and distributed simulation software framework including basic simulation service models and agent-based simulation models was put forward firstly. Compared to the other simulation projects, the framework has many advantages, such as platform-independence, scalability, hierarchical, separation from modeling framework and simulation framework, etc.The features of the components and time management algorithm of the framework were described in outline. According to the framework, a prototype of agent-based distributed simulation environment, named as ADSimE (Agent-Based Distributed Simulation Environment) was implemented based on Java. The ADSimE takes full advantage of the idea of object-oriented design. Domain experts can carry through distributed simulation of all fields on ADSimE with great flexibility and simplicity.A communication system of the ADSimE was presented. The whole architecture of the communication system was also established. An agent-based communication framework including XML and KQML was proposed, which can enforce the communication between different agents, and benefit to the cooperation and collaboration between agents, enforce the flexibility and extensibility of the simulation system. The communication protocol between agents in the framework of communication system was based on KQML, and XML as a wrapper of the KQML messages.ABMS methodology was proposed to the uppermost and effective means for the M&S of satellite systems, including multi-satellite system and a single satellite system. The process of ABMS for multi-satellite systems was described firstly, hi addition, the modeling methods and simulation framework were also studied. The library of capabilities and algorithm for satellite agent model were developed to simulate the multi-satellite system. Therefore, a prototype system of agent-based simulation for anti-satellite operation demonstration, named ASSAO was developed based on ADSimE. The ABMS in the M&S of multi-satellite system was validated from the simulation of orbit dynamics, collision avoidance and anti-satellite operation. Researches were made to the M&S of a single satellite too. Two softwares, GN&C V1.0 for the design and simulation of GN&C subsystems of a satellite and SatComm V1.0 for the analysis and evaluation of communication payload&subsystem of a satellite, were developed based on the thoughts of ABMS.The features, details of how to implement and models of the two softwares were described in outline. The two softwares validated the ABMS in the research of M&S for a single satellite.
引文
[1] Waldrop M著,陈玲译.复杂:诞生于秩序与混沌边缘的科学.生活·读书·新知三联书店,1997.
    [2] http://www.santafe.edu
    [3] http://www.swarm.org
    [4] http://www.econ.iastate.edu/tesfatsi/
    [5] http://www.c3.lanl.gov/~rocha/complex/index.htm
    [6] http://www.complex.org/
    [7] Namatame A. Agent-Based simulation. Dept. of Computer Science, National Defense Academy, Yokosuka, JAPAN.
    [8] Green D G. Hierarchy, complexity and agent based models. In Our Fragile World: Challenges and Opportunities for Sustainable Development. UNESCO, Paris.
    [9] Marcenac P. Emergence of Behaviors in Natural Phenomena Agent Simulation, in Proceedings of the Third International Conference on Complex Systems: From Local Interactions to Global Phenomena, Eds R Stocker, H Jelinek, Bohdan Durnota and T Bossomaier, pp. 284-289, Albury, Australia, 1996.
    [10] Marcenac P, Giroux S, Grasso J R, Lahaie F. Simulating Emergent Behaviors: An Application to Volcanoes. In Proceedings of Summer Computer Simulation Conference, Portland, OR, July 1996.
    [11] Calderoni S, Marcenac P. Emergence of Earthquakes by Multi-agent Simulation. in Proceedings of European Simulation Multi-Conference, ESM'97, Istambul, Turquey, SCS Int. Publishers, pp. 665-669, 1997.
    [12] Multi Agent Simulation. http://www.maths.ox.ac.uk/~sumpter/beesim/index.html
    [13] Theodoropoulos G. Distributed Simulation of Agent-Based Systems Case for Support. Http://www.cs.bham.ac.uk/~gkt/Research/PDES/pdes-mas.pdf
    [14] 廖守亿,戴金海.基于多Agent的天战系统建模与仿真方法研究.计算机仿真,2003,20(1):18-21.
    [15] Loral System Company. ModSAF Software Architecture Design and Overview Document, December 1993.
    [16] 汪成为,郑小军,彭木昌著.面向对象分析、设计与应用.北京:国防工业出版社,1992.9.
    [17] 约翰.霍兰著,周晓牧等译.隐秩序——适应性造就复杂性.上海科技教育出版社,2001.
    [18] 约翰.霍兰著,陈禹等译.涌现.上海:上海科技出版社,2001.
    [19] Basu J, Pryor T Q, Arnold T. Aspen: A Microsimulation Model of Economy. Sandia Report #SAND96-2459, Sandia National Laboratories. Albuquerque. NM, October 1996. http://www.sandia.gov
    [20] Hewitt C. Viewing Control Structures as Patterns of Passing Messages. Artificial Intelligence, Volume8, number3, pages 323-364, McGraw-Hill, New York, USA, 1997.
    [21] Uhrmacher A M, Gugler K. Distributed, Parallel Simulation of Multiple, Deliberative Agents. Proceedings of the 14th Workshop on Parallel and Distributed Simulation, 2000.
    [22] Uhrmacher A M, Tyschler P, et al. Modeling and Simulation of Mobile Agents. Future Generation Computer Systems, 2000.
    [23] Agent Working Group. Agent Technology Green Paper. Object Management Group Document ec/99-08-06 version 0.8, 1999.
    [24] Anderson J, Evans M. A Generic Simulation Systems for Intelligent Agent Designs. Applied Artificial Intelligence, Volume9, Number5, October, 1995, pp. 527-562.
    [25] Dooley K, Corman S. Agent-based Generic and Emergent Computational models of Complex Systems, under review at Encyclopedia of Life Support Systems.
    [26] Wooldridge M J, Jennings N R. Agent Theories, Architectures, and Language: A Survey, in Wooldridge and Jennings Eds., Intelligent Agents, ppl-22, Bediin Springer-Vedag, 1995. 99 Appendix A Sample Cable Amplifier Network Topology Table A. 1: Portion of topology from the cable amplifier network in, 1995.
    [27] Ting-Peng Liang, Jin-Shiang Huang. A Framework for Applying intelligent agents to electronic trading. Decision Support Systems, 2000, 28: 305-317.
    [28] Lee K J, Chang Y S, Lee J K. Time-bound negotiation framework for electronic commerce agents. Decision Support Systems, 2000: 319-331.
    [29] Jennings N R, Corera J M, et al. Developing Industrial Multi-agent System. In: Proceedings of the First International Conference on Multi-agent Systems, (ICMA-95), 423-430.
    [30] Franklin S, Graesser A. Is it an agent, or just a program? A Taxonomy for autonomous agent. In: Proceedings of the Third international Workshops on Agent Theories, Architectures, and Language, Springer-Verlag, 1996: 62-71.
    [31] Wooldridge M J. Agent-based Software Engineering. IEE Proc. Software Engineering. 1997, 144(1): 26-37.
    [32] Shoham Y. Agent-oriented programming. Artificial Intelligence, 1993, 60: 51-92.
    [33] Lane D M, Mcfadzean A G. Distributed problem solving and real-time mechanisms in robot architectures. Engineering Application intelligence, 1994, 7(2): 105-117.
    [34] Wooldridge M J, Jennings N R. Intelligent agents: Theory and practice. Knowledge Engineering Reviews, 1995, 10(2): 115-152.
    [35] Rao A S, Georgeff M P. BDI Agents: from theory to practice. Proceedings of lst International Conference on Multi-Agent Systems(ICMAS-95), San Francisco, ACM Press, 1995: 312-319.
    [36] Ferber J. Multi-agent systems, an introduction to distributed artificial intelligence. Addison-Wesley, 1999.
    [37] 史忠植.智能主体及其应用.北京:科学出版社,2001.
    [38] Rumbaugh J, Blaha M, et al. Object-Oriented Modeling and Design. Prentice-Hall, 1991.
    [39] Jacobson I, Christerson M, et al. Object-Oriented Software Engineering. A Use Case Driven Approach. ACMPress, 1992.
    [40] Rumbaugh J, Jacobson I, et al. The Unified Modeling Language Reference Manual. Addison-Wesley, 1998.
    [41] Shoham Y. Agent-oriented programming. Artificial Intelligence, 1993, 60(1): 51-92.
    [42] 代树武,孙辉先.航天器自主运行技术的进展.宇航学报,2003,24(1):17-22.
    [43] Truszkowski W, Hallock H. Agent Technology from a NASA Perspective. http://isd.gsfc.nasa.gov/Papers/DOC/AgentTechpaper.pdf
    [44] Goddard Agent Group Working Paper. "LOGOS Requirements and Design Document", http://agents.gsfc.nasa.gov/products.html
    [45] Pell B, Bernard D E, Chien S A, Gat E, Muscettola N, et al. A Remote Agent Prototype for Spacecraft Autonomy. SPIE Proceedings, Volume 2810, Denver, CO, 1996.
    [46] Muscettola N, Nayak P P, Pell B, Williams B C. Remote Agent: To Boldly Go Where No AI Systems Has Gone Before. 1998 Artificial Intelligence. Invited Talk, IJCAI-97, Nayoga, Japan.
    [47] Surka D M, Brito M C, Harvey C G. The Real-Time ObjectAgent Software Architecture for Distributed Satellite Systems. 2001 IEEE Aerospace Conference Proceedings, Big Sky, Montana, March 2001.
    [48] Schetter T, Campbell M, Surka D M. Multiple Agent-Based Autonomy for Satellite Constellation. the Second International Symposium on Agent Systems and Applications, September 2000, Zurich, Switzerland.
    [49] Princeton-satellite systems web-page, http://www.psatellite.com
    [50] Wagner G, Tulba F. Agent-Oriented Modeling and Agent-Based Simulation. In Proceedings of 5th int Workshop on Agent-Oriented Information Systems(AOIS-2003), ER2003 Workshops, Springer-Verlag, LNCS, 2003.
    [51] Boero R. Some Methodological Issues of Agent Based Models in Social Sciences. http://www.unisi.it/santachiara/aree/conf_phd_econ2003/conference siena/papers/boero.pdf.
    [52] Brian J L B, Kiel D, Elliott E. Adaptive agents, intelligence, and emergent human organization: Capturing complexity through agent-based modeling. PNAS 2002 99: 7187-7188; published online before print May 7 2002, 10. 1073/pnas. 092078899.
    [53] Bankes S C. Agent-based modeling: A revolution? Proc Natl Acad Sci U S A. 2002 May 14; 99(Suppl. 3): 7199-7200. DOI: 10. 1073/pnas. 072081299.
    [54] Henrickson L, McKelvey B. Foundations of "new" social science: Institutional legitimacy from philosophy, complexity Science, postmodemism, and agent-based modeling. Proc Natl Acad Sci U S A. 2002 May 14; 99 (Suppl. 3): 7288-7295.
    [55] 邓宏钟,谭跃进,迟妍.一种复杂系统研究方法——基于多智能体的整体建模仿真方法.系统工程,2000,18(4):73-77.
    [56] 冯珊,唐超,闵君,沈冲.用于复杂系统建模与仿真的面向智能体技术.管理科学学报,1999,2(2):71-76.
    [57] 赵怀慈,黄莎白.基于Multi-Agent的海上搜救仿真研究及应用.计算机工程与应用,2002.20:41-43.
    [58] 李群,宣慧玉.基于Agent仿真技术在经济建模中的应用.系统工程理论方法应用,2001,10(3):22l-225.
    [59] 邓宏钟,王军民,谭跃进.基于多智能体的整体建模仿真方法在经济系统中的应用研究.计算机应用研究,2001,10期:24-26.
    [60] 赵怀慈.基于Agent的建模与仿真方法研究.工学博士学位论文,中国科学院沈阳自动化研究所,2003.
    [61] http://hla.dmso.mil/
    [62] 曹军海.基于Agent的离散事件仿真建模框架及其在系统RMS建模与仿真中的应用研究.工学博士学位论文,装甲兵工程学院,2002.
    [63] Helbing D. Agent-Based Simulation of Traffic Jam, Crowds, and Supply Networks. in Proceeding of the IMA'Hot Topics' Workshop, IMA, Minneapolis, MN. 2003.
    [64] Barret C. Simulation Sciences it Relates to Data/Information Fusion and C2 Systems, Briefing Slides, Los Alamos(1997).
    [65] Schreiber D. The Emergence of Parties: An Agent-Based Simulation. http://www.bol.ucla.edu/~dschreib/EmergingParties/EmergenceParties6-24-01.pdf
    [66] http://transims.tsasa.lanl.gov
    [67] 约翰.L.卡斯蒂著,王千祥,权利宁译.虚实世界——计算机仿真如何改变科学的疆域.上海科技教育出版社,1998.
    [68] Raney B, Nagel K. An Agent-Based Simulation Model of Swiss Travel: First Results. 3rd Swiss Transport Research Conference, March 19-21, 2003.
    [69] Epstein J M, Axtell R L. Growing Artificial Societies: Social Science from the Bottom Up. MIT Press, Cambridge, MA. 1996.
    [70] http://www.simwofld.co.uk/
    [71] Srbljinovic A, Penzar D, Rodik P, Kardov K. Agent-Based Modeling of Ethnic Mobilization: The Former Yugoslavia Case. 1st LA Conference on Computational Social Science and Social Complexity: AB Modeling in Social Sciences, 2002.
    [72] Derek W B, Oliveirs F S. Agent-based Simulation: An Application to the New Electricity Trading Arrangements of England and Wales. IEEE-TEC, special issue: Agent Based Computational Economics, 2001.
    [73] Xuwei Chen. Agent-Based Simulation of Evacuation Strategies under Different Road Network Structures. http://www.ucgis.org/summer03/studentpapers/xuweichen.pdf.
    [74] Pryor R J, Basu N, Quint T. Development of Aspen: a microanalytic simulation model of the U. S. economy. SAND96-0434 Distribution. Unlimited Release Category UC-905. Sandia National Laboratories, 1996.
    [75] Basu N, Pryor R J. Growing a market economy. SAND-97-2093 Distribution. Unlimited Release Category UCD905. Sandia National Laboratories, 1997.
    [76] Arthur WB, Holland J H, Lebaron B, Palmer RG, Tayler P. in The Economy as a Complex Evolving System II, Santa Fe Institute Studies in the Sciences of Complexity, eds. Arthur W B. , Durlauf S. &Lane D. Addison-Wesley, Reading MA, Proceeding Vol. 27, pp. 15-42. 1997.
    [77] Arthur W B, Holland J H, LeBaron B, Palmer R G, Tayler P. Asset Pricing Under Endogenous Expectations, Santa Fe Institute Paper, 1996.
    [78] Tesfatsion L. Introduction to the JEDC Special Issue on Agent-Based Computational Economics, Journal of Economic Dynamics and Control, Vol. 25, pp. 281-293, 2001.
    [79] Ilachinski A. Irreducible Semi - Autonomous Adaptive Combat (ISAAC): An Artificial - Life Approach to Land Combat. Center for Naval Analyses Research Memorandum CRM 97 -61. 1997.
    [80] Ilachinski A. Towards a Science of Experimental Complexity: An Artificial-Life Approach to Modeling Warfare. Center for Naval Analyses, Alenandria, Virginia, USA.
    [81] Hunt C W, Saias I. Complexity-Based Modeling and Simulation: Modeling Innovation at the Edge of Chaos. Presented at 1998 Command and Control Research and Technology Symposium , Monterey , California , 1998. http://www.dodccrp.org/Proceedings/DOCS/wcd00000/wcd000ec.htm.
    [82] North M J , Rimmer M , Macal C M . Why the Navy Needs TSUNAMI. http://www.nd.edu/~swarm03/Program/Abstracts/ NorthSwarm2003 .pdf.
    [83] Jeffrey RC. The Use of Agent-based Models in Military Concept Development. Proceedings of the 2002 Winter Simulation Conference. E. Yucesan, C. H. Chen, J. L. Snowdon, and J. M. Charnes, eds. 2002.
    [84] Darbyshire P, Abbass H, Barlow M, McKay B. A Prototype Design for Studying Emergent Battlefield Behavior through Multi-Agent Simulation. Technical report, Victoria University of Technology, Australia.
    [85] Heinze C, Smith B, Cross M. Thinking quickly: Agents for modeling air warfare.. In Proceedings of the 9th Australian Joint Conference on Artificial Intelligence (AI'98). Brisbane, Australia, 1998.
    [86] Coradeschi S, Karlsson L, Torne A. Intelligent agents for aircraft combat simulation. in 6th Conf. on Computer Generated Forces and Behavioral Representation, Orlando (FL, USA). 1996.
    [87] Standish R K. Complexity Growth in Artificial Life. http://parallel.acsu.unsw.edu.au/rks.
    [88] Ray. An approach to the synthesis of life. Artificial Life-Ⅱ, Addison-Wesley. 1991.
    [89] Railsback S. Complex Adaptive Systems Meets the Real World: Agent-based Simulation for Ecological Management and Research. http://math.humboldt.edu/~simsys/.
    [90] Dong Won Yi, Soung Hie Kim, Nak Hyun Kim. Combined Modeling with Multi-Agent Systems and Simulation: Its Application to Harbor Supply Chain Management. Proceeding of the 35th Hawaii International Conference on System Sciences, 2002.
    [91] Szirbik N, Wagner G, Tulba F. Agent-Based Modeling and Simulation of Distributed Business Processes in Supply Networks. The International Workshop on Modeling & Applied Simulation, MAS2003 Program.
    [92] Marcenac P. Emergence of Earthquakes by MultiAgent Simulation. http://www.univ-reunion.fr/~geomas.
    [93] Marcenac P. Emergence of Behaviors in Natural Phenomena Agent-Simulation. in Proceedings of the Third International Conference on Complex Systems: From Local Interactions to Global Phenomena, Eds. R. Stocker, H. Jelinek, Bohdan Durnota and T. Bossomaier, 284-289, Albury, Australia, 1996.
    [94] http://repast.sourceforge.net/
    [95] http://www.trook.edu/es/dynamics/models/ascape
    [96] Daila J, Uzcagegui M. GALATEA: A multi-agent simulation platform.http://ches.ing.ula.ve/investigacion/ARTICULOS/JACINTO/MSNN-JDMU00.pdf.
    [97] Sloman A, Poli R. SIM_AGENT: A toolkit for exploring agent designs, in Intelligent Agents——Ⅱ: Agent Theories Architectures and Languages (ATAL-95), M. Wooldridge, J. Mueller, and M. Tambe, Eds. New York: Springer-Verlag, 1996, pp. 392-407.
    [98] Courdier R, Guerrin F, Andriamasinoro F H, Paillat J M. Agent-based simulation of complex systems: application to collective management of animal wastes. Journal of Artificial Societies and Social Simulation. Vol. 5, No. 3.
    [99] Courdier R, Marcenac P, Calderoni S. Zooming on a Multiagent Simulation System: from the Conceptual Architecture to the Interaction Protocol. IREMIA, University of La Reunion.
    [100] Lees M, Logan B. Simulating Agent-Based Systems with HLA: The Case of SIM_AGENT——Part Ⅱ. In: Proceedings of the 2003 European Simulation Interoperability Workshop, European Office of Aerospace R&D, Simulation Interoperability Standards Organization and Society for Computer Simulation International, 2003.
    [101] Baxter J W, Richard T H. Virtual Battlefield Simulation Agents, Experience with the SIM_AGENT Toolkit. ftp://ftp.cs.bham.ac.uk/pub/authors/B.S.Logan/AAAI-98/papers/baxter.ps.gz.
    [102] 李宏亮.基于Agent的复杂系统分布仿真.工学博士学位论文,国防科技大学研究生院,2001.
    [103] 胡峰,孙国基.航天仿真技术的现状及展望.系统仿真学报,1999,11(2).
    [104] Hagedorn J, etc. A Computer Graphics Pilot Project: Spacecraft Mission Support with an Interactive Graphics Workstation. Proceedings of the Society for Computer Simulation, 1986.
    [105] Kazuhiro Kimura. Satellite Orbit Analysis and Design by Virtual Reality. http://track.sfo.jaxa.jp/spaceops98/paper98/track4/4b006.pdf
    [106] Ferebee M J, Troutman P A, Monell D W. Satellite Systems Design/Simulation Environment: A Systems Approach to Pre-Phase A Design. In Proceedings of the 35th Aerospace Sciences Meeting and Exhibit(Reno, NV, Jan. 6-9). AIAA, Reston, VA.
    [107] 贺勇军,戴金海,李连军.复杂多卫星系统的综合建模与仿真.系统仿真学报,2004,16(5):871-875.
    [108] 段彬,韩潮.卫星星座仿真系统的设计和实现.计算机仿真,2002,19(6):37-38.
    [109] 向开恒,肖业伦.卫星星座的系统仿真研究.北京航空航天大学学报,1999,25(6).
    [110] 王江云,彭晓源,王行仁.基于HLA的卫星分布仿真系统设计与实现.计算机工程与设计,2004,25(5):700-702.
    [111] 孙兆伟,徐国栋,林晓辉,曹喜滨.小卫星设计、分析与仿真一体化系统.系统仿真学报,2001,13(5):623-626.
    [112] 张山,贝超,杨嘉伟.微小卫星数字化综合仿真试验系统研究.系统仿真学报,2003,15(6):765-767.
    [113] Bonabeau E. Agent-based modeling: Methods and techniques for simulating human systems. Proc Natl Acad Sci U S A. 2002 May 14; 99 Suppl 3: 7280-7.
    [114] Bonabeau E, Hunt L C, Gaudiano P. Agent-Based Modeling for Testing and Designing Novel Decentralized Command and Control System Paradigms. the 8th International Command and Control Research and Technology Symposium, June 17-19, 2003, National Defense University Washington, DC.
    [115] Huigen M G. Agent Based Modeling in Land Use and Land Cover Change Studies. Interim Report IR-03-044. International Institute for Applied Systems Analysis Schlossplatz. A-2361 Laxenburg, Austria.
    [116] Dawn C P, Berger T, Manson S M. Agent-Based Models of Land-Use and Land-Cover Change. Report and Review of an International Workshop. October 4-7, 2001, Irvine, California, USA.
    [117] Klugl F, Puppe F. The Multi-Agent Simulation Environment SeSAm. In: H. Kleine Buning (Hrsg.): Proceedings des Workshops "Simulation in Knowledge-based Systems", Paderborn, April 1998 (=Report tr-ri-98-194, Reihe Informatik, Universitat Paderborn), 1998.
    [118] Marietto M B, et al. Requirements Analysis of Multi-Agent-Based Simulation Platforms: State of the Art and New Prospects. Proceedings of Multi-Agent Based Simulation Workshop, Bologna, Italy, 15-19 July, 2002.
    [119] Wickenberg T, Davidsson P. On Multi Agent Based Simulation of Software Development Processes. http://www.ide.hk-r.se/~pdv/Papers/MABS2002.pdf
    [120] Davidsson P. Multi Agent Based Simulation: Beyond Social Simulation. In Moss, S. and Davidsson, P. (Eds). Multi-Agent-Based Simulation, Second International Workshop. MABS 2000, Boston, M. A., pp. 97-107.
    [121] Baydar C. Agent-Based Modeling and Simulation of Store Performance for Personalized Pricing. Proceedings of the 2003 Winter Simulation Conference, pp. 1759-1764.
    [122] Sawhney A, Walsh K, Mulky A R. Agent-Based Modeling and Simulation in Construction. Proceedings of the 2003 Winter Simulation Conference, pp. 1541-1547.
    [123] Odell J, et al. Modeling Agents and their Environment: The Physical Environment. Journal of Object Technology, Vol. 2(2), March-April2003, pp. 43-51.
    [124] Odell J, Parunak H V, Fleischer M. Modeling Agents and their Environment: The Communication Environment. Journal of Object Technology, 2(3), May-June 2003: 39-52.
    [125] Baas N A, Emmeche C. On Emergence and Explanation. SFI Publication 97-02-008. Santa Fe, N. Mex.: Santa Fe Institute. 1997.
    [126] Reynolds C W. Flocks, Herds and Schools: A distributed behavior model. SIGGRAPH'87 Conference Proceedings, Computer Graphics, 1987, 21(4): 25-34.
    [127] Sommerville I. Software Engineering. Addison Wesley. 1998.
    [128] Mills D, Dyer M, Linger R. Cleanroom software engineering. In: IEEE Software, 1987, 4 (2).
    [129] Zeigler B P, Praehofe H, Kim T G. Theory of modeling and simulation(2nd Edition). San Diego, USA, Academic Press, 2000.
    [130] 戴金海,廖守亿,张玉锟.基于Multi-Agent的天战分布式仿真演示系统综合论证报告.国防科学技术报告,2002.7.
    [131] Benjamin P, Erraguntla M, Delen D, Mayer R. Simulation Modeling at Multiple levels of abstraction. Proceedings of the 1998 Winter Conference. D. J. Medeiros, E. F. Watson, J. S. Carson and M. S. Manivannan, eds.
    [132] Good D, Young W. Mathematical methods for digital systems development. In S. Prehn and W. J. Toetenel, editors, VDM'91: Formal Soflware Development Methods, Proceedings of the Fourth International Symposium of VDM Europe, LNCS, 552, volume 2, pages 406-430. Springer-Verlag, 1991.
    [133] Spivey J. Understanding Z: A Specification Language and its Formal Semantics. Cambridge University Press. 1988.
    [134] Jones C B. Systematic Software Development Using VDM. Prentice Hall International. 1990.
    [135] Jennings N, Sycara K, Wooldridge M. A roadmap of agent research and development. Autonomous Agents and Multi-Agent Systems, 1998, 1(1): 7-38.
    [136] Miller R J. A Review of Behavioral Animation. Computer&Graphics, 1999, Vol. 23, No. 1: 127-143.
    [137] 党岗,刘华峰,程志全等.多Agent虚拟环境中的行为建模及其动画表现.系统仿真学报增刊,200l(11):142-145.
    [138] Tu Xiaoyuan, Terzopoulos D. Artificial Fishes: Physics, Locomotion, Perception, Behavior. Proceedings of SIGGRAPH'94: 43-50.
    [139] Bryan L A, Joseph B. Hap: A Reactive, Adaptive Architecture for Agents. Technical Report CMU-CS-91-147, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, June 1991.
    [140] Beer R D. Intelligence as adaptive behavior: an experiment in computational neuroethology. Academic Press, 1990.
    [141] Mase P. Designing autonomous agents: theory and practice from biology to engineering and back. MIT Press, 1991.
    [142] Sutton R S. Reinforcement learning architectures from animates. Computer Simulation of Adaptive Behavior in Animates, Computer Animation'94, IEEE Computer Society Press, 1994.
    [143] Cliff D, Harvey I, Husbands P. Explorations in evolutionary robotics. Adaptive Behavior, 1993.
    [144] Manna Z, Worlper P. Synthesis of communicating processes from temporal logic specifications. ACM Trans on Programming Language System, 1984, 6(1): 68-93.
    [145] http://www.fas.org/spp/military/program/warning/sbirs.htm. Space Based Infrared System, 1999. 12. 18.
    [146] Woods E, Queeney T. Multi-sensor Detection and Tracking of Tactical Ballistic Missile Using Knowledge-Based State Estimation. Signal Processing, Sensor Fusion and Target Recognition Ⅲ, Proc. SPIE [C], 1994.
    [147] 廖守亿,戴金海.复杂系统基于Agent的建模与仿真设计模式及软件框架.计算机仿真.已录用,待刊.
    [148] 廖守亿,戴金海.基于Agent的建模与仿真设计模式及软件框架.系统仿真学报,2005,17(4):863-866.
    [149] http://www.dmso.mil/
    [150] 高志年,邢汉承.基于HLA的智能仿真支撑环境研究.计算机工程,2002,28(4):13-14.
    [151] 金士尧,李宏亮,党岗,王召福,刘晓建.复杂系统计算机仿真的研究与设计.中国工程科学,2002,4(4):52-57.
    [152] Chandy K M, Misra J. Asynchronous distributed simulation via a sequence of parallel computations. Communications of the ACM. 1981, 24(11), 198-205.
    [153] Jefferson D, Sowizral H. Fast concurrent simulation using the time warp mechanism, in Proceedings of the SCS Distributed Simulation Conference, SCS Simulation Series, 1985, pp. 63-69.
    [154] Chandy K M, Misra J. Distributed Simulation: A Case Study in Design and Verification of Distributed Programs. IEEE Transactions on Software Engineering. 1978, SE-5(5): 440-452.
    [155] Bryant R E. Simulation of Packet Communication Architecture Computer Systems. Computer Science Laboratory. Cambridge, Massachusetts, Massachusetts Institute of Technology, 1977.
    [156] Misra J. Distributed Discrete-Event Simulation. ACM Computing Surveys, 18(1): 39-65, 1986.
    [157] Fujimoto R M. Parallel and Distributed Simulation, Proceedings of the 1999 Winter Simulation Conference, 1999, pp. 122-131.
    [158] Boukerche A, Tropper C. Parallel Simulation on the Hypercube Multiprocessor. Distributed Simulation(PADS'95). pp. 68-77, 1995.
    [159] Bain W L, Scott D S. An Algorithm for Time Synchronization in Distributed Discrete Event Simulation. In B. Unger and D. Jefferson, Editors, Proceedings of the SCS Multiconference on Distributed Simulation, 19(3), pp. 30-33. SCS, Feb. 1988.
    [160] Groselj B, Tropper C. The Time-of-next-event Algorithm. In B. Unger and D. Gefferson, editor, Proceedings of the SCS Multiconference on Distributed Simulation, 19(3), pp. 25-29. SCS, February 1998.
    [161] Ayani R. Parallel Simulation Using Conservative Time Windows, Proc. Of the 1992 Winter Simulation Conference, pp. 709-717, 1992
    [162] Jefferson D. Virtual Time. ACM Transactions on Programming Languages and Systems, 7(3): 404-425, 1985.
    [163] Jefferson D, Sowizral H. Fast Concurrent Simulation Using the Time Warp Mechanism. In P. Reynolds, editor, Distributed Simulation 1985, pp. 63-69, La Jolla, California, 1985. SCS-The Society for Computer Simulation, Simulation Councils, Inc.
    [164] Fujimoto R M. Parallel and Distributed Simulation Systems. Proceedings of the 2001 Winter Simulation Conference. 2001, pp. 147-157.
    [165] Das S R, Fujimoto R M. Adaptive Memory Management and Optimism Control in Time Warp. ACM Transactions on Modeling and Computer Simulation 7(2): 239-271.
    [166] Gafni A. Rollback Mechanisms for Optimistic Distributed Simulation Systems. In. B. Unger and D. Jefferson, editors, Proceedings of the SCS Multiconference on Distributed Simulation, 19(3), pp. 61-67. SCS, February 1998.
    [167] Fujimoto R M. Parallel Discrete Event Simulation. Commtmications of the ACM, 33(10), pp. 30-53, October 1990.
    [168] Prakash A, Subramanian R. Filter: An Algorithm for Reducing Cascaded Rollbacks in Optimistic Distributed Simulation. In A. H. Rutan, editor, Proceedings of 24th Annual Simulation Symposium, New Orleans, Louisiana, USA, April 1-5, 1991., pp. 123-132. IEEE Computer Society Press, 1991.
    [169] Sokol L M, Briscoe D P, Wieland A P. MTW: A Strategy for Scheduling Discrete Simulation Events for Concurrent Execution. In Proc. ofSCS Multiconf. On Distributed Simulation, pp. 34-42, 1988.
    [170] Ferscha A. Parallel and Distributed Simulation of Discrete Event Systems. Handbook of Parallel and Distributed Computing, McGraw-Hill, 1995.
    [171] Labrou Y, Finin T, Peng Y. Agent communication Language: the Current Landscape. IEEE Intelligent Systems, 1999, 14(2): 45-52.
    [172] Extensible Markup Language(XML). http://www.w3.org/XML/.
    [173] Harold E R. XML Bible. IDG Books Worldwide Inc., 1999.
    [174] The XML Industry Portal. http://www.xml.org.
    [175] Sun Microsystems: The Java Language Environment: A White Paper. 1995, http://javasoft.com/whitePaper/java-whitepaper_l.html
    [176] Gasser L, Kakugawa K. Mace3j; Fast flexible distributed simulation of large, large-grain multi-agent systems. In Proceedings of AAMAS-2002, Bologna, July 2002.
    [177] Uhrmacher A M, Schattenberg B. Agents in Discrete Event Simulation. In European Simulation Symposium-ESS'98, Nottingham, October 1998. SCS.
    [178] Vincent R, Horling B, Lesser V. An Agent Infrastructure to Build and Evaluate MAS: The Java Agent Framework and Multi-Agent System Simulator. In Infrastructure for Agents, MAS and Scalable MAS, LANI1887, Springer-Verlag, pp. 102-127, 2000.
    [179] Pontius P, Gleason D. Modeling and Simulation for System-of-Systems Engineering. Raytheon Company. Http://www.spacecoretech.org/coretech2000/Papers/Software/Raytheon_paper.html.
    [180] Das A, etc. TechSat21 Space Missions Using Collaborating Constellations of Satellites. SSC 98-Ⅵ-1. 1998.
    [181] 张铃,张钹.遗传算法的机理研究.软件学报,2000,11(7):945-952.
    [182] 廖良才,谭跃进等.模糊仿真理论综述及探讨.模糊系统与数学,2000,14(3):72-79.
    [183] http://www.stk.com
    [184] 廖守亿,戴金海.与STK软件实现系统集成.系统仿真技术及其应用,’2003学术论文集,Vol.5:328-331.
    [185] 廖守亿,戴金海.基于Agent的建模与仿真在太空作战仿真中的应用.计算机仿真,2003,增刊:383-386.
    [186] 任萱编著.人造地球卫星轨道力学.长沙:国防科技大学出版社,1988.
    [187] Wertz J R, Larson W J. Space Mission Analysis and Design. Third Edition. Torrance, California: Microcosm Press. 1999.
    [188] 陈琪锋,廖守亿等.卫星制导、导航与控制分系统模型及软件技术报告.国防科学技术报告,2003.9.
    [189] Roddy D. Satellite Communications. Third Edition. Canada: McGraw-Hill Companies, Inc. 1996.
    [190] 陈道明主编.通信卫星有效载荷技术.北京:宇航出版社,2001.
    [191] 廖守亿,赵健康.卫星有效载荷性能分析.国防科学技术报告,2003.9.
    [192] 陈振国,齐怀亮等编著.卫星地球站数字通信设备.北京:人民邮电出版社,1995.
    [193] Wiener N. Cybemetics or Control and Communication in the Animal and Machine, MIT Press, Cambridge On the Human Use of Human Beings: Cybernetics and Society, 1948.
    [194] 萧昆涛主编,科学认识史论,南京:江苏人民出版社,1995.
    [195] 乔非,沈荣芳,吴启迪.系统理论、系统方法、系统工程——发展与展望.系统工程,1996,14(5):5-10.
    [196] 陈禹六.大系统理论及其应用.北京:清华大学出版社,1988.
    [197] 邓聚龙.灰色系统理论教程.武汉:华中理工大学出版社.1990.
    [198] 钱学森.开创复杂巨系统的科学与技术.系统工程理论与实践,1995,1:1-2.
    [199] 钱学森,戴汝为,于景元.一个科学新领域——开放的复杂巨系统及其方法论.自然杂志,1990,13(1):3-10.
    [200] 谭跃进,高世楫,周曼殊著.系统学原理.国防科技大学出版社,1996.
    [201] 吴祥兴等编著.混沌学导论.上海科学技术文献出版社,1997.
    [202] 黄昀.分形与应用.物理通报,1999,2:1-4.
    [203] 孙万鹏.第3种科学.山东人民出版社,1998.
    [204] Cowan C A. Conference Opening Remarks In: Pines A, Meltzer D, et al eds. Complexity, Metaphors, Models and Reality. New York: Addision Wesley, 1994, 1~4.
    [205] 戴汝为.复杂巨系统科学——一门21世纪的科学.自然杂志,1996,19(4):187-197.
    [206] Holland J. Hidden order How adaptation builds complexity, Addison-Wesley Publishing Company Inc, 1995.
    [207] 中国系统工程学会.复杂巨系统理论·方法·应用.北京:科学技术文献出版社,1994.
    [208] 约翰.霍兰著,孙雍君等译.科学的终结.呼和浩特:远方出版社,1997,290-329.
    [209] 王寿云,于景元,戴汝为,汪成为,钱学森,徐元季.开放的复杂巨系统.杭州:浙江科学技术出版社,1996.p286.
    [210] M.盖尔曼著,杨建邺,李湘涟等译.夸克和美洲豹——简单性与复杂性的奇遇.湖南科学技术出版社,1998.
    [211] 苗东升.论复杂性.自然辩证法通讯,2000,22(6):87-92.
    [212] 于景元,刘毅,马昌超.关于复杂性研究.系统仿真学报.2002,14(11):1417-1424.
    [213] Gallagher R,Appenzeller J.超越还原论.戴汝为.复杂性研究论文集.1999.
    [214] 操龙兵,戴汝为.综合集成研讨厅的软件体系结构.软件学报,2002,13(8):1430-1435.
    [215] 崔霞,戴汝为,李耀东.群体智慧在综合集成研讨厅体系中的涌现.系统仿真学报,2003,15(1):146-153.
    [216] 王浣尘.综合集成系统开发的系统方法思考.系统工程理论方法应用.2002,11(1):1-7.
    [217] 廖守亿,戴金海.复杂适应系统及基于Agent的建模与仿真方法.系统仿真学报,2004,16(1):113-117.
    [218] 苗东升.复杂性研究的现状与展望.系统辩证学学报,2001,9(4):3-9.
    [219] Agent Based Modeling..http://www.cadrc.calpoly.edu/pdf/JSVoss_120400.pdf.
    [220] 王正中.复杂系统仿真方法及应用.计算机仿真.2001,18(1):3-6.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700