基于MAS的分布式成像卫星系统任务规划与控制问题研究
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摘要
由现代智能成像小卫星组成的分布式成像卫星系统是未来对地观测卫星系统发展的主要趋势,分布式成像卫星系统具有智能性和分布性的特点,是一种“敏捷”卫星系统。分布式成像卫星系统的任务规划与控制是在充分考虑分布式成像卫星系统特点的基础上,面向动态观测环境,将多个观测任务没有冲突地分配给分布式成像卫星系统中最合适的卫星执行,并通过自动推理得到各个卫星的具体动作方案,从而自主控制卫星完成各个观测任务。目前,无论是在国内还是国外,对分布式成像卫星系统的任务规划与控制问题的研究都是一个崭新的前沿课题,而且随着现代小卫星系统、分布式卫星系统的快速发展,以及对多星任务规划技术、卫星自主运行技术研究的不断深入,使得本文问题的研究无论是在理论上还是应用上都有非常重要的意义。本文在深入了解分布式成像卫星系统的组成和运行特点的基础上,提出了分布式成像卫星系统的任务规划与控制框架,探索了分布式成像卫星系统的星群任务规划方法、卫星自主控制模型及其求解算法,并最终开发实现了一个原型系统。本文的主要研究内容和创新研究成果如下:
首先,在分析成像卫星工作原理及分布式成像卫星系统工作过程的基础上,将整个问题分为两个层次的决策子问题进行求解。根据分布式成像卫星系统的分布性和智能性特点,采用Agent及多Agent系统(Multi-Agent System,简称MAS)的思想研究分布式成像卫星系统,给出了一种高可靠性的分布式成像卫星系统MAS结构及智能成像卫星Agent的分层混合结构模型,并以此为基础,分析了基于MAS的分布式成像卫星系统的任务规划与控制机理与特点,提出了基于MAS的任务规划与控制框架。
其次,提出了基于多Agent协商的分布式动态任务规划方法,对传统的合同网协商协议进行改进,提出了基于约束的诚实合同网协议,采用招投标的方式对星群进行任务调度,重点研究了投标活动中任务插入导致的时间窗口约束和电源约束的满足性判断方法,给出了相应的检验算法。根据分布式成像卫星系统的运行特点,提出了基于推进剂消耗和任务均衡指标的各种优化规则,并通过实例研究对各种规则的性能进行了比较,给出了规则使用策略。
第三,分析了基于层次任务网络(Hierarchical Task Network,简称HTN)的规划方法对卫星自主控制问题的适用性,给出了相应的求解框架。首先采用规划域定义语言建立了智能成像卫星的规划域模型,然后采用基于HTN的规划方法对卫星自主控制问题进行了求解,开发了两种基于任务网络的导引式状态空间搜索算法。通过实例分析验证了基于HTN的规划方法可以实现对卫星自主控制问题的快速求解。
最后,设计实现了一个星座形式的分布式成像卫星系统任务规划与控制原型系统,给出了该系统的一个应用实例,综合验证了本文提出的基于多Agent协商的分布式动态任务规划方法、基于HTN规划的卫星自主控制方法、相应的算法以及原型系统的有效性。
Distributed imaging satellite system composed of modern intelligent small imaging satellites is the main earth observing satellite application system in the future. Distributed imaging satellite system is a kind of agile satellite system that is intelligent and distributed. The problem of mission planning and control for the distributed imaging satellite system is defined as: considering the characteristics of the distributed imaging satellite system and the requirement of dynamic observing environment sufficiently, assign various observing missions to the satellites among distributed imaging satellite system optimally. Then generate the detail action plan of every satellite through automatically reasoning, so as to control the satellite autonomously to complete the observing missions. The mission planning and control problem for distributed imaging satellite system is still a brand new problem for researchers either inside or outside the country at present. As the development of modern small satellite and distributed satellite system rapidly, and the research of mission planning technology for multi-satellites and autonomous satellite technology growing on, the investigation on such problems is of great significance both from the theory or application viewpoints. Based on the understanding of components and operation of distributed imaging satellite system, this thesis provides a framework for mission planning and control of distributed imaging satellite system, investigates mission planning technology for satellite cluster, autonomous control model and algorithm for satellite. At last, a prototype of mission planning and control system for distributed satellite system is developed. The main contents and fruits of this paper are outlined as follows:
Firstly, this thesis divides the whole problem into two sub decision problems based on analyzing the imaging principle of satellite and the operating process of satellite system. The method based on agent and multi-agent system (MAS) is used to research distributed imaging satellite system according to the distributed and intelligent attributes of distributed imaging satellite system, so as to a kind of MAS structure with high reliability for distributed imaging satellite system and a hierarchical mixed agent structure for single satellite are designed separately. Based on these structures, this thesis analyzes the mechanism of mission planning and control based on MAS, and proposes the mission planning and control framework based on MAS for distributed imaging satellite system.
Secondly, this thesis proposes a distributed dynamic mission planning approach based on multi-agent negotiation. This approach improves on the traditional contract-net protocol and a constraints-based honest contract-net protocol is designed eventually, which schedules the observing missions of satellite cluster by means of bidding. The means of feasibility test for mission insertion is presented and the algorithms for verifying the satisfiability of corresponding time window constraint and power constraint are given in detail. According to the operation character of distributed satellite system, the rules of optimizing the fuel consumption and the index of mission trade-off are proposed. This thesis also compares the performance of these rules, and suggests the strategy of utilizing rules.
Thirdly, this thesis analyzes the applicability of HTN-based planning approach for autonomous control problem of satellite. The domain model of intelligent satellite is constructed using planning domain definition language, and then the autonomous control problem of satellite is solved by the HTN-based planning approach. This thesis provides two guided state space search algorithms based on task network. At last, an example is given to demonstrate that the HTN-based planning approach can solve the autonomous control problem of satellite effectively.
Lastly, this thesis devises and realizes the prototype of mission planning and control system for constellation. In addition, this thesis gives an example and solves it by the prototype system. The results verify the validity of the proposed distributed dynamic mission planning approach for distributed imaging satellite system, HTN-based autonomous control approach for single satellite, corresponding algorithms, and prototype system.
首先,在分析成像卫星工作原理及分布式成像卫星系统工作过程的基础上,将整个问题分为两个层次的决策子问题进行求解。根据分布式成像卫星系统的分布性和智能性特点,采用Agent及多Agent系统(Multi-Agent System,简称MAS)的思想研究分布式成像卫星系统,给出了一种高可靠性的分布式成像卫星系统MAS结构及智能成像卫星Agent的分层混合结构模型,并以此为基础,分析了基于MAS的分布式成像卫星系统的任务规划与控制机理与特点,提出了基于MAS的任务规划与控制框架。
其次,提出了基于多Agent协商的分布式动态任务规划方法,对传统的合同网协商协议进行改进,提出了基于约束的诚实合同网协议,采用招投标的方式对星群进行任务调度,重点研究了投标活动中任务插入导致的时间窗口约束和电源约束的满足性判断方法,给出了相应的检验算法。根据分布式成像卫星系统的运行特点,提出了基于推进剂消耗和任务均衡指标的各种优化规则,并通过实例研究对各种规则的性能进行了比较,给出了规则使用策略。
第三,分析了基于层次任务网络(Hierarchical Task Network,简称HTN)的规划方法对卫星自主控制问题的适用性,给出了相应的求解框架。首先采用规划域定义语言建立了智能成像卫星的规划域模型,然后采用基于HTN的规划方法对卫星自主控制问题进行了求解,开发了两种基于任务网络的导引式状态空间搜索算法。通过实例分析验证了基于HTN的规划方法可以实现对卫星自主控制问题的快速求解。
最后,设计实现了一个星座形式的分布式成像卫星系统任务规划与控制原型系统,给出了该系统的一个应用实例,综合验证了本文提出的基于多Agent协商的分布式动态任务规划方法、基于HTN规划的卫星自主控制方法、相应的算法以及原型系统的有效性。
Distributed imaging satellite system composed of modern intelligent small imaging satellites is the main earth observing satellite application system in the future. Distributed imaging satellite system is a kind of agile satellite system that is intelligent and distributed. The problem of mission planning and control for the distributed imaging satellite system is defined as: considering the characteristics of the distributed imaging satellite system and the requirement of dynamic observing environment sufficiently, assign various observing missions to the satellites among distributed imaging satellite system optimally. Then generate the detail action plan of every satellite through automatically reasoning, so as to control the satellite autonomously to complete the observing missions. The mission planning and control problem for distributed imaging satellite system is still a brand new problem for researchers either inside or outside the country at present. As the development of modern small satellite and distributed satellite system rapidly, and the research of mission planning technology for multi-satellites and autonomous satellite technology growing on, the investigation on such problems is of great significance both from the theory or application viewpoints. Based on the understanding of components and operation of distributed imaging satellite system, this thesis provides a framework for mission planning and control of distributed imaging satellite system, investigates mission planning technology for satellite cluster, autonomous control model and algorithm for satellite. At last, a prototype of mission planning and control system for distributed satellite system is developed. The main contents and fruits of this paper are outlined as follows:
Firstly, this thesis divides the whole problem into two sub decision problems based on analyzing the imaging principle of satellite and the operating process of satellite system. The method based on agent and multi-agent system (MAS) is used to research distributed imaging satellite system according to the distributed and intelligent attributes of distributed imaging satellite system, so as to a kind of MAS structure with high reliability for distributed imaging satellite system and a hierarchical mixed agent structure for single satellite are designed separately. Based on these structures, this thesis analyzes the mechanism of mission planning and control based on MAS, and proposes the mission planning and control framework based on MAS for distributed imaging satellite system.
Secondly, this thesis proposes a distributed dynamic mission planning approach based on multi-agent negotiation. This approach improves on the traditional contract-net protocol and a constraints-based honest contract-net protocol is designed eventually, which schedules the observing missions of satellite cluster by means of bidding. The means of feasibility test for mission insertion is presented and the algorithms for verifying the satisfiability of corresponding time window constraint and power constraint are given in detail. According to the operation character of distributed satellite system, the rules of optimizing the fuel consumption and the index of mission trade-off are proposed. This thesis also compares the performance of these rules, and suggests the strategy of utilizing rules.
Thirdly, this thesis analyzes the applicability of HTN-based planning approach for autonomous control problem of satellite. The domain model of intelligent satellite is constructed using planning domain definition language, and then the autonomous control problem of satellite is solved by the HTN-based planning approach. This thesis provides two guided state space search algorithms based on task network. At last, an example is given to demonstrate that the HTN-based planning approach can solve the autonomous control problem of satellite effectively.
Lastly, this thesis devises and realizes the prototype of mission planning and control system for constellation. In addition, this thesis gives an example and solves it by the prototype system. The results verify the validity of the proposed distributed dynamic mission planning approach for distributed imaging satellite system, HTN-based autonomous control approach for single satellite, corresponding algorithms, and prototype system.
引文
[1] 高云国.现代小卫星及其相关技术.光学精密工程,1999,7:16-21.
[2] 林来兴.现代小卫星与纳卫星技术发展.国际太空,2002,8:25-28.
[3] 马元申 , 于小红 , 尹志忠 . 现代小卫星技术及其发展对策 . 国防技术基础,2003,5:13-15.
[4] 罗开元.航天及其基础技术未来发展分析.中国航天,2002,3:26-30.
[5] 李智斌.航天器智能自主控制技术发展现状与展望.航天控制,2002,4:1-7.
[6] 卢波.国外空间探测发展分析与展望. 空间科学学报,2000,S1:80-92.
[7] 潘科炎.航天器编队飞行及其关键技术的开发.遥测遥控,2003,5:9-15.
[8] 张云华,张祥坤,姜景山.空间虚拟探测技术及其发展趋势.系统工程与电子技术,2005,12:2006-2009.
[9] 闻新 , 马文弟 , 周露 . 小卫星编队飞行的应用模式分析及展望 . 中国航天,2005,8:40-43.
[10] 闻新,张伟.卫星编队飞行技术的进展及建议.国际太空,2005,1:9-14.
[11] 夏南银,张守信,穆鸿飞.航天测控系统.北京:国防工业出版社,2002.
[12] 范丽,张育林,曾国强.小卫星星座及其自主运行技术.上海航天,2002,4:29-32.
[13] 代树武,孙辉先.航天器自主运行技术的进展.宇航学报,2003,1:17-22.
[14] Mandl D.Experimenting with Sensor Webs Using Earth Observing 1.IEEE Aerospace Conference, Big Sky, MT, 2004.
[15] Sherwood R, Chien S, Davies A, et al. Realtime Decision Making on EO-1 Using Onboard Science Analysis. SPIE 2004 Remote Sensing of the Atmosphere, Ocean, Enviroment, and Space, Honolulu, Hawaii, 2004.
[16] Koratkar A, Grosvenor S, Jung J, et al. Autonomous Multi-sensor Coordination: The Science Goal Monitor. SPIE 2004 Remote Sensing of the Atmosphere, Ocean, Enviroment, and Space, Honolulu, Hawaii, 2004.
[17] Goddard Space Flight Center, EO-1 Mission page: http://EO-1.gsfc.nasa.gov.
[18] Martin M, Stallard M J. Distributed Satellite Missions and Technologies – The TechSat 21 Program. In Proceeding of the 1999 AIAA Space Technology Conference and Exposition, Albuquerque, 1999.
[19] Das A, R Cobb. TechSat21- Space Missions Using Collaborating Constellations of Satellites. Proceeding of the 12th Annual AIAA/USU Conference of Small Satellites, Logan, UT, 1998.
[20] Kim Luu, Maurice Martin, Mike Stallard, et al. University Nanosatellite Distributed Satellite Capabilities to Support TechSat 21. Proceeding of the 12th Annual AIAA/USU Conference of Small Satellites, Logan, UT, 1998.
[21] John L Mohammed. Mission Planning for a Formation-Flying Satellite Cluster.
[22] Rabideau G, Knight R, Chien S, et al. Iterative Repair Planning for Spacecraft Operations in the ASPEN System. International symposium on Artificial Intelligence Robotics and Automation in Space, Noordwijk, The Netherlands, 1999.
[23] Underhill, Friedman B A, Wong J, et al. Three Corner Sat Constellation – Arizona State University: Management; Electrical Power System; Structure, Mechnaisims, Thermal, and Radiation; Attitude/Orbit Determination and Control; ASU Micropropulsion Experiment; and Integration. 13th AIAA/USU Conference on Small Satellites, Logan, UT, 1999.
[24] Martin M. University Nanosatellite Program. Proceedings of the IAF Symposium, Redondo Beach, CA, 1999.
[25] Subrata Das, Curt Wu, Walt Truszkowski. Enhanced Satellite Constellation Operations via Distributed Planning and Scheduling. In Proc. of the 6th International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS-01), Montreal, Canada, 2001.
[26] Bornschlegl E, Guettier C, Poncet J-C. Automatic Planning for Autonomous Spacecrafts Constellation. In Proceedings of 2nd NASA Workshop on Planning & Scheduling for Space, San Francisco USA, 2000.
[27] Guettier C, Poncet J-C. Multi-Levels Planning for Spacecraft Autonomy. In proceeding of 6th International Symposium on Artificial Intelligence, Robotics and Automation in Space, Montreal Canada, 2001.
[28] Poncet J C, Guettier C, Le Lann G, et al. Constraint-Based Layered Planning and Distributed Control for an Autonomous Spacecraft Formation. In Proceedings of the 1st ESA Workshop on Space Autonomy, 209-219. Noordwijk, NL: European Space Agency, 2001.
[29] Hyuckchul Jung, Milind Tambe, Anthony Barrett, and Bradley Clement. Enabling Efficient Conflict Resolution in Multiple Spacecraft Missions via DCSP. In Proceedings of the NASA workshop on Planning and Scheduling, 2002.
[30] Solotorevsky G, Gudes E, and Meisels A. Distributed Constraint Satisfaction Probl ems a Model and Application. Submitted to Constraint Journal, 1997.
[31] Paul Zetocha, Lance Self, Ross Wainwright, et al. Commanding and Controlling Satellite Clusters. IEEE Intelligent Systems, 2000, 15(6): 8-13.
[32] 林来兴.卫星编队飞行动力学仿真及其应用.中国空间科学技术,2005,2:26-33.
[33] 杨维廉.近圆轨道控制的分析方法.中国空间科学技术,2003,5:1-5.
[34] 梁甸农,朱炬波,董臻.小卫星分布式雷达.中国基础科学,2004,6:7-10.
[35] 胡 行 毅 . 编 队 小 卫 星 应 用 系 统 的 地 面 运 控 管 理 技 术 综 述 . 国 际 太空,2004,7:21-26.
[36] 张健, 戴金海. 分布式卫星系统(DSS) 及其自主控制技术分析. 航天控制,2004,5:16-19.
[37] Muscettola N, Pandurang Nayak P, Pell B, et al. Remote Agent: To bodly go where no AI system has gone before”, NASA Ames Research Center, 1998.
[38] Muscettola N. HSTS: Integrating planning and scheduling. In Fox, M, and Zweben, M, Eds, Intelligent Scheduling, Morgan Kaufman, 1994.
[39] 李平. ESA 的星上自主验证计划(PROBA).飞行器测控学报,2000,3: 52-60.
[40] Chien S, Knight R, Stechert A, et al. Using Iterative Repair to Improve Responsiveness of Planning and Scheduling. In Proceedings of the Fifth International Conference on Artificial Intelligence Planning and Scheduling, Breckenridge, CO, April 2000.
[41] Pell B, Bernard D, Chien S, et al. A remote agent prototype for spacecraft autonomy. In Proceedings of the SPIE Conference on Optical Science, Engineering and Instrumentation, 1996.
[42] Cichy B, Chien S, Schaffer S. Validating the EO-1 Autonomous Science Agent. International Workshop on Planning and Scheduling for Space, Darmstadt, Germany, June 2004.
[43] Teston F, Creasey R. PROBA:ESA’s Autonomy and Technology Demonstration Mission. In 48th Interntional Astronatical Congress, Turin, 1997.
[44] 代树武.成像侦察卫星调度问题研究.国防科技大学博士学位论文.2004.
[45] 刘洋.航天侦察多星多地面站任务规划问题研究.国防科技大学博士学位论文.2005.
[46] Karia Sycara, Steven F Roth, Norman Sadeh, et a1. Distributed Constrained Heuristic Search. IEEE Transactions on Systems, Man and Cybernetics, 1991, 21(6): 1446-1461.
[47] Grace Yuh-jiun Lin, James J Solberg. Integrated Shop Floor Control Using Autonomous Agents.IIE Transactions, 1992, 24(3): 57-71.
[48] 刘伟,金雁.基于合同网的作业车间分布式合作调度策略.上海交通大学学报,1992,26(2): 77-82.
[49] Reid G Smith. The Contract-Net Protocol: High Level Communication and Control for a Distributed Problem Solver. IEEE Trans Computers, 1980, 29(12): 1104-1113.
[50] Klaus Fischer. Knowledge-based Reactive Scheduling in a Flexible Manufacturing System. IFIP Transactions B: Computer Applications in Technology, 1993(B-15): 1-18.
[51] Carlos Ramos. An Architecture and a Negotiation Protocol for the Dynamic Scheduling of Manufacturing Systems. Proceedings- IEEE International Conference on Robotics and Automation. IEEE, 1994, 3161-3166.
[52] Carlos Ramos. Task Negotiation for Distributed manufacturing System. Proceedings of the IEEE International Symposium on Assembly and Task Planning. IEEE, 1995, 259-264.
[53] Carla P Gomes, Austin Tate, Lyn Thomas. Distributed Scheduling Framework. Proceedings of the International Conference on Tools with Artificial Intelligence. IEEE, 1996, 3849-3850.
[54] Koji Morikawa, Takeshi Furuhashi, Yoshiki Uchikawa. Evolution of CIM System with Genetic Algorithm. IEEE Conference on Evolutionary Computation-Proceedings (2). IEEE, 1994, 746-749.
[55] Rachel Lau, Joel Favrel. Intelligent Scheduling Agent for Distributed Decision-making. Proceedings of the IEEE Conference on Decision and Control(4). IEEE, 1996, 3849-3850.
[56] Kap Hwan Kim, Jong Wook Bae, Joon Yub Song, et al. Distributed Scheduling and Shop Floor Control Method. Computers & Industrial engineering, 1996, 31(3-4): 583-586.
[57] Kap Hwan Kim, Jun Yeob Song, Ki Hong Wang. Negotiation Based Scheduling for Items with Flexible Process Plans. Computers & Industrial Engineering, 1997, 31(3-4): 785-788.
[58] Kouiss K, Pierreval H, Mebarki N. Using Multi-agent Architecture in FMS for Dynamic Scheduling. Journal of Intelligent Manufacturing, 1997, 8(1): 41-47.
[59] F P Maturana, D H Norrie. Multi-Agent Mediator Architecture for Distributed Manufacturing. Journal of Intelligent Manufacturing, 1996, 7(4): 257-270.
[60] A L Ananda, G S H Tan, L F Lau. Distributed Scheduling Algorithms for the Astra Virtual machine. Australian Computer Science Communications, 1997,19(1): 218-227.
[61] Albert D Baker. Survey of Factory Control Algorithms That can be Implemented in a Muti-Agent Heterachy: Dispatching, Scheduling, and Pull. Journal of Manufacturing Systems, 1998,17(4): 297-320.
[62] Siddhartha Bhattacharyya, Gary J Koehler. Learning by Objectives for Adaptive Shop-floor Scheduling. Decision Science, 1998, 29(2): 347-375.
[63] P C Pendharkar. A Computational Study on Design and Performance Issues of Multi-Agent Intelligent Systems for Dynamic Scheduling Enviroments. Expert Systems with Application, 1999(16): 121-133.
[64] Yu Lian, Ohsato Ario, Kawakami Terujyu, et al. CORBA-based Design and Development of Distributed Scheduling Systems: an Application to Flexible Flow Shop Scheduling Systems. Proceedings of the IEEE International Conference on SMC (4). IEEE(SMC); SCJ; SICE; RSJ; JSME IEEE, 1999:IV-522-IV -527.
[65] Knotts Gary, Dror Moshe, Hartman Bruce C. Agent-based Project Scheduling. IIE Transactions, 2000, 32(5): 387-401.
[66] 赵博.结构化集成调度系统理论及基于该理论的虚拟车间智能支撑平台的体系结构研究.大连:大连理工大学,2000.
[67] Chen Y Y, Fu L C, Chen Y C. Multi-agent Based Dynamic Scheduling for a Flexible Assembly System. Proceedings-IEEE International Conference on Robotics and Automation (3). IEEE, 1998, 2122-2127.
[68] Ouelhadj D, Hanachi C, Bouzouia B. Multi-agent System for Dynamic Scheduling and Control in Manufacturing Cells. IEEE International Conference on Robotics and Automation (3). IEEE, 1998, 2128-2133.
[69] Ouelhadj D, Hanachi C, Bouzouia B, et al. Multi-Contract Net Protocol for Dynamic Scheduling in Flexible Manufacturing Systems (FMS). Proceedings- IEEE International Conference on Robotics and Automation (3). IEEE, 1999, 1114-1119.
[70] R J Rabelo, L M Camarinha-matoe. Multi-Agent-Based Agile Scheduling. Robotics and Autonomous Systems, 1999, 27(1):15-28.
[71] 王艳红,尹朝万,张宇.基于多代理和规则调度的敏捷调度系统研究.计算机集成制造系统,2000,6(4): 45—49.
[72] A Brun, A Portioli. Agent-based Shop-Floor Scheduling of Multi Stage Systems. Cpmputers and Industrial Engineering, 1998, 37(1): 457-460.
[73] Weiming Shen, Douglas H Norrie. Dynamic Manufacturing Scheduling Using Both Functional and Resource Related Agents. Intergrated Comuter-Aided Engineering, 2001, 8(1):17-30.
[74] Nils J.Nilsson. Artificial Intelligence: A New Synthesis. China Machine Press. 2000, 361-400.
[75] Stuart Russell, Peter Norvig. Artificial Intelligence: A Modern Approach (Second Edition). Beijing: Posts & Telecom Press, 2004.
[76] 冯健翔.广义人工智能基础研究.北京:宇航出版社,1999.
[77] Fikes R E, Nilsson N J. STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving. In Artificial Intelligence, Vol No 3-4, pp189-208.
[78] M FoxD Long. PDDL2.1: An Extension to PDDL for Expressing Temporal Planning Domains. Unpublished manuscript, 2001.
[79] A Barrett, D Weld. Partial Order Planning: Evaluating Possibleeciency Gains. Articial Intelligence, 1994, 67(1):71-112.
[80] A Gerevini, L Schubert. Accelerating Partial-Order Planners: Some Techniques for Effective Search Control and Pruning. Articial Intelligence Research, 1996, 5: 95-137.
[81] R Kambhampati, A Mali, B Srivastava. Hybrid Planning for Partially Hierarchical Domains. In Proc. 15th Nat. Conf. AI, 1998.
[82] Blum A, Furst M. Fast Planning through Planning Graph Analysis. In Proc.14thInt. Joint Conf. AI, 1995.
[83] Kautz H., McAllester D, Selman B. Encoding Plans in Propositional Logic. In Proc. 5th Int. Conf. Principles of Knowledge Representation and Reasoning, 1996.
[84] D McDermott. Using Regression Graphs to Control Search in Planning. Artificial Intelligence, 1999, 109(1-2):111–160.
[85] J Hoffmann. Extending FF to Numerical State Variables. The Proceedings of the 15th European Conference on Artificial Intelligence, Lyon, France, July 2002.
[86] Malte Helmert. Complexity Results for Standard Benchmark Domains in Planning. Artificial Intelligence, accepted.
[87] D E Smith, J Frank, A K Jonsson. Bridging the Gap between Planning and Scheduling. Knowledge Engineering Review, 15(1), 2000.
[88] J. Walton, Models for the Management of Satellite-based Sensors, Ph.D. Dissertation, Massachusetts Institute of Technology, 1993.
[89] 文 沃 根 . 高 分 辨 率 IKONOS 卫星影像 及 其产品的 特性 . 遥 感 信息 . 2001.1:37-38.
[90] Gordon Petrie. Monitoring Iraq – Imagery Options for Monitoring and Gathering Intelligence. GI News. 2003,1-2.
[91] M. Lema?tre, G. Verfaillie, Selecting and Scheduling Observations of Agile Satellites, Aerospace Science and Technology. 6 (2002) 367-381.
[92] Philippe Baptiste, W P M Nuijten. Constraint Based Scheduling: Applying Constraint Programming to Scheduling Problems. Kluwer Academic Press, 2001
[93] Bartak R.On the Boundary of Planning and Scheduling: a Study. Proceedings of the Eighteenth Workshop of the UK Planning and Scheduling Special Interest Group, Manchester, UK, 1999.
[94] Fikes R E, Nilsson N J. STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving. In Artificial Intelligence, Vol No 3-4, pp189-208.
[95] Allen J, Hendler J, Tate A. Readings in Planning. Morgan Kaufmann, 1990.
[96] Allen J. towards a General Theory of Action and Time. Artificial Intelligence, 1984, 23(2), 123-154.
[97] 杨祥林,诸波,徐宁等.空间光通信技术.南京邮电学院学,2002,3:25-31.
[98] 蔡燕民,陈刚,董作人.空间激光通信系统进展.激光与光电子学进展,2000,5:1-6.
[99] Analytical Graphics Inc. Satellite Tool Kit 5.0. 2003.
[100] 杨颖,王琦.STK 在计算机仿真中的应用.北京:国防工业出版社,2005.
[101] 魏青,薛国宇.微小卫星液化气推进技术.上海航天,2003,5:46-49.
[102] J McCarthy, P J Hayes. Some Philosophical Problems from the Standpoint of Artificial Intelligence. In B. Meltzer and D Michie, editors, Machine Intelligence 4. Edinburgh University Press, 1969.
[103] Minsky M. The Society of Mind. New York: Simon & Schuster, 1986.
[104] Wooldridge M, Jennings N. Intelligent Agents: Theory and Practice. The Knowledge Engineering Review, 1995, 10(2): 115-152.
[105] Mare H Debugging. Multi-Agent System. Information and Software Technology, 1995, 37(2): 102-112.
[106] Hewitt C. A Universal Modular Actor Formalism for AI. In Proceedings of the 3rd International Joint Conference on Artificial Intelligence (IJCAJ-73), 1973: 235-245.
[107] 张洁,高亮,李培根.多 Agent 技术在先进制造中的应用.北京:科学出版社,2004.
[108] Shohan Y. Agent Oriented Programming. Artificial Intelligence, 1993, (60): 51-92.
[109] Brooks R A. Intelligence without Representation. Artificial Intelligence, 1991, 47:139-159.
[110] Jennings N R et al. Agent-based Business Process Man Agent, Int. Journal of Cooperative Information System, 1996, 5(2-3):105-130.
[111] Sycara K P, Wooldridge M. Agents’98: Proceedings of the Second International Conference on Autonomous Agent, ACM Press, 1998.
[112] Rao A S, Georgeff M P. Formal Models and Decision Procedures for Multi-Agent System. Technical Note 61, Australian AI Institute, Level 6, 171 La Trobe Stree, Melbourne, Australia, 1995.
[113] Bratman M E. Intention, Plans and Practical Reason. Harvard University Press, Cabridge, MA.
[114] Jennings N R. Specification and Implementation of Belief Joint-Intention Architecture for Collaborative Problem Solving. Journal of Intelligent and Cooperative Information Systems, 1993, 2(3): 289-318.
[115] Ingrand F F, Georgeff M P, Rao S. An Architecture for Real-Time Reasoning and System Control. IEEE Expert, 1992, 7(6).
[116] 史忠植.高级人工智能.北京:科学出版社,1998.
[117] Minsky M, Riecken D. A Conversation with Marvin Minsky about Agent. Communication of the ACM, 1994, 37(7):23-29.
[118] Muller J P, Wooldridge M, Jennings N R. Intelligent Agent, Ⅲ, LNAI Volume 1193. Springer, Berlin, 1996.
[119] Gerhard Weiss. Multiagent Systems. The MIT Press, 2000.
[120] Simon H A. Models of Bounded Rationality. Cambridge, Mass. MIT Press, 1982-1997,1-3.
[121] Minsky M. The Society of Mind. New York: Simon & Schuster, 1985.
[122] 雷鸣.智能加工监测及知识协同处理的研究.华中理工大学博士论文,1997.
[123] Jennings N R, Sycara K, Wooldridge M. A Roadmap of Agent Research and Development. Autonomous Agents and Muti-Agent Systems, 1998, 10(2):199-215.
[124] 何炎祥.Agent 和多 Agent 系统的设计与应用.武汉:武汉大学出版社,2001.
[125] 张云勇.移动 agent 技术.北京:清华大学出版社,2003.
[126] Lesser V, Decker K, Wanger T. Evolution of the GPGP/TAEMS Domain-independent Coordination Framework. Autonomous Agents and Multi-Agent Systems, 2004(9): 87-143.
[127] Genesereth M R, Ketchet S P. Software Agents. Communication of the ACM, 1993,37(7): 48-53.
[128] Gaines B R, Norrie D H, Lapsley A Z. An Intelligent Information System Supporting the Virtual Manufacturing Enterprise. Proceedings of 1995 IEEE International Conference on Systems, Man and Cybernetics. Vancouver, 1995, 10.
[129] Thomas Schetter, Mark Campbell, Derek Surka. Multiple Agent-based Autonomy for Satellite Constellations. Artificial Intelligence, 2003, 145:147-180.
[130] Pell B, D E Bernard, S A Chien, et al. An Autonomous Spacecraft Agent Prototype. Autonomous Robots, 5(1), 1998.
[131] Ari K Jonsson, Paul H Morris, Nicola Muscettola, et al. Planning in interplanetary space: Theory and practice. In Proceedings of the Fifth International Conference on Artificial Intelligence Planning and Scheduling, 2000.
[132] M Lemaitre, G. Verfaillie, F. Jouhaud, J. Lachiver, and N. Bataille. How to manage the new generation of agile earth observation satellites? In Proceedings of the International Symposium on Artificial Intelligence, Robotics and Automation in Space, 2000.
[133] J. Pemberton. Towards scheduling over-constrained remote sensing satellites. In Proceedings of the 2d InternationalWorkshop on Planning and Scheduling for Space, 2000.
[134] W. Wolfe and S. Sorensen. Three scheduling algorithms applied to the earth observing domain. Management Science, 46(1), 2000.
[135] J C Pemberton, L G Greenwald. On the Need for Dynamic Scheduling of Imaging Satellite. International symposium on Future Intelligent Earth Observing Satellites, 2002.
[136] Reid G Smith. Framework for Distributed Problem Solving. SAE Preprints, Int Jt Conf on Artif Intell (2), 1979:836-841.
[137] Saad A, Kawamura K, Johnson M E et al. Evaluating a Contract Net-based Heterachical Scheduling Approach for Flexible Manufacturing. IEEE International Symposium on Assembly and Task Planning (ISATP’95), Pittsburgh, Pennsylvania, 1995.
[138] Saad A, Salama A, Kawamura K et al. A Bidirectional Contract Net for Production Planning and Scheduling. Proceedings of the UC/IAMS Workshop formanufacturing Research, Cincinnati, Ohio, 1994.
[139] 李道亮,傅泽田,田东.智能系统:基础方法及其在农业中的应用.北京清华大学出版社,2004.
[140] M W P Savelsbergh. The Vehicle Routing Problem with Time Windows: Minimizing Route Duration. INFORMS Journal on Computing, 1992, 4(2):146-154.
[141] Rojanasoonthon, Siwate. Parallel Machine Scheduling With Time Windows. PH.D, University of Texas at Austin, 2004.
[142] 贺仁杰.成像侦察卫星调度问题研究.国防科技大学博士学位论文.2004.
[143] 李菊芳.航天侦察多星多地面站任务规划问题研究.国防科技大学博士学位论文.2005.
[144] 刘洋.成像侦察卫星动态重调度模型、算法及应用研究.国防科技大学博士学位论文.2005.
[145] Erol K, Hendler J, and Nau D. HTN Planning: Complexity and Expressivity. To appear in Proc. AAAI-94, 1994.
[146] 谷长兴,冯志勇.基于 HTN 的供应链优化策略.计算机应用,2003,23(10):103～105.
[147] D Nau, H. Muoz-Avila, Y. Cao, et al. Total-Order Planning with Partially Ordered Subtasks. IJCAI-2001, Seattle, August, 2001.
[148] 范玉顺,曹军威.多代理系统理论、方法与应用.北京:清华大学出版社,2002.
[149] 朱彦伟,杨乐平,陈钦.基于多 Agent 技术的卫星星座设计分析.系统仿真学报,2004,9:2006-2008.
[150] Fabio Bellifemine, Giovanni Caire, Tiziana Trucco. JADE Programmer’s Guide. TILAB, 2005.
[151] Fabio Bellifemine, Giovanni Caire, Tiziana Trucco. JADE Administrator’s Guide. TILAB, 2005.
[152] Foundation for Intelligent Physical Agents. FIPA00023, FIPA Agent Management Specification[ EB /OL ]. http://www.fipa.org/specs/fipa00023/, 2002.
[153] 刘路,斯蒂芬 麦京.小卫星与国际灾害监测星座.中国航天,2004,6:18-21.
[154] 李伯林,左烨. dmc+4 小卫星在国际灾害监测中的应用与评价.遥感学报,2005,4:468-473.
[155] 林来兴.发展我国小卫星星座和测控技术.飞行器测控学报,2000,3:17-22.
[156] 汤君友,杨桂山,赵锐.HT-1 微小卫星及其在国土资源调查中的应用.航天返回与遥感,2003,3:42-46.
[157] 尤政,戴汩.”航天清华一号”微小卫星及其图像处理.遥感学报,2001,3:176-182.
[158] 钱曾波,刘静宇,肖国超.航天摄影测量.北京:解放军出版社,1992:23-40.
[2] 林来兴.现代小卫星与纳卫星技术发展.国际太空,2002,8:25-28.
[3] 马元申 , 于小红 , 尹志忠 . 现代小卫星技术及其发展对策 . 国防技术基础,2003,5:13-15.
[4] 罗开元.航天及其基础技术未来发展分析.中国航天,2002,3:26-30.
[5] 李智斌.航天器智能自主控制技术发展现状与展望.航天控制,2002,4:1-7.
[6] 卢波.国外空间探测发展分析与展望. 空间科学学报,2000,S1:80-92.
[7] 潘科炎.航天器编队飞行及其关键技术的开发.遥测遥控,2003,5:9-15.
[8] 张云华,张祥坤,姜景山.空间虚拟探测技术及其发展趋势.系统工程与电子技术,2005,12:2006-2009.
[9] 闻新 , 马文弟 , 周露 . 小卫星编队飞行的应用模式分析及展望 . 中国航天,2005,8:40-43.
[10] 闻新,张伟.卫星编队飞行技术的进展及建议.国际太空,2005,1:9-14.
[11] 夏南银,张守信,穆鸿飞.航天测控系统.北京:国防工业出版社,2002.
[12] 范丽,张育林,曾国强.小卫星星座及其自主运行技术.上海航天,2002,4:29-32.
[13] 代树武,孙辉先.航天器自主运行技术的进展.宇航学报,2003,1:17-22.
[14] Mandl D.Experimenting with Sensor Webs Using Earth Observing 1.IEEE Aerospace Conference, Big Sky, MT, 2004.
[15] Sherwood R, Chien S, Davies A, et al. Realtime Decision Making on EO-1 Using Onboard Science Analysis. SPIE 2004 Remote Sensing of the Atmosphere, Ocean, Enviroment, and Space, Honolulu, Hawaii, 2004.
[16] Koratkar A, Grosvenor S, Jung J, et al. Autonomous Multi-sensor Coordination: The Science Goal Monitor. SPIE 2004 Remote Sensing of the Atmosphere, Ocean, Enviroment, and Space, Honolulu, Hawaii, 2004.
[17] Goddard Space Flight Center, EO-1 Mission page: http://EO-1.gsfc.nasa.gov.
[18] Martin M, Stallard M J. Distributed Satellite Missions and Technologies – The TechSat 21 Program. In Proceeding of the 1999 AIAA Space Technology Conference and Exposition, Albuquerque, 1999.
[19] Das A, R Cobb. TechSat21- Space Missions Using Collaborating Constellations of Satellites. Proceeding of the 12th Annual AIAA/USU Conference of Small Satellites, Logan, UT, 1998.
[20] Kim Luu, Maurice Martin, Mike Stallard, et al. University Nanosatellite Distributed Satellite Capabilities to Support TechSat 21. Proceeding of the 12th Annual AIAA/USU Conference of Small Satellites, Logan, UT, 1998.
[21] John L Mohammed. Mission Planning for a Formation-Flying Satellite Cluster.
[22] Rabideau G, Knight R, Chien S, et al. Iterative Repair Planning for Spacecraft Operations in the ASPEN System. International symposium on Artificial Intelligence Robotics and Automation in Space, Noordwijk, The Netherlands, 1999.
[23] Underhill, Friedman B A, Wong J, et al. Three Corner Sat Constellation – Arizona State University: Management; Electrical Power System; Structure, Mechnaisims, Thermal, and Radiation; Attitude/Orbit Determination and Control; ASU Micropropulsion Experiment; and Integration. 13th AIAA/USU Conference on Small Satellites, Logan, UT, 1999.
[24] Martin M. University Nanosatellite Program. Proceedings of the IAF Symposium, Redondo Beach, CA, 1999.
[25] Subrata Das, Curt Wu, Walt Truszkowski. Enhanced Satellite Constellation Operations via Distributed Planning and Scheduling. In Proc. of the 6th International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS-01), Montreal, Canada, 2001.
[26] Bornschlegl E, Guettier C, Poncet J-C. Automatic Planning for Autonomous Spacecrafts Constellation. In Proceedings of 2nd NASA Workshop on Planning & Scheduling for Space, San Francisco USA, 2000.
[27] Guettier C, Poncet J-C. Multi-Levels Planning for Spacecraft Autonomy. In proceeding of 6th International Symposium on Artificial Intelligence, Robotics and Automation in Space, Montreal Canada, 2001.
[28] Poncet J C, Guettier C, Le Lann G, et al. Constraint-Based Layered Planning and Distributed Control for an Autonomous Spacecraft Formation. In Proceedings of the 1st ESA Workshop on Space Autonomy, 209-219. Noordwijk, NL: European Space Agency, 2001.
[29] Hyuckchul Jung, Milind Tambe, Anthony Barrett, and Bradley Clement. Enabling Efficient Conflict Resolution in Multiple Spacecraft Missions via DCSP. In Proceedings of the NASA workshop on Planning and Scheduling, 2002.
[30] Solotorevsky G, Gudes E, and Meisels A. Distributed Constraint Satisfaction Probl ems a Model and Application. Submitted to Constraint Journal, 1997.
[31] Paul Zetocha, Lance Self, Ross Wainwright, et al. Commanding and Controlling Satellite Clusters. IEEE Intelligent Systems, 2000, 15(6): 8-13.
[32] 林来兴.卫星编队飞行动力学仿真及其应用.中国空间科学技术,2005,2:26-33.
[33] 杨维廉.近圆轨道控制的分析方法.中国空间科学技术,2003,5:1-5.
[34] 梁甸农,朱炬波,董臻.小卫星分布式雷达.中国基础科学,2004,6:7-10.
[35] 胡 行 毅 . 编 队 小 卫 星 应 用 系 统 的 地 面 运 控 管 理 技 术 综 述 . 国 际 太空,2004,7:21-26.
[36] 张健, 戴金海. 分布式卫星系统(DSS) 及其自主控制技术分析. 航天控制,2004,5:16-19.
[37] Muscettola N, Pandurang Nayak P, Pell B, et al. Remote Agent: To bodly go where no AI system has gone before”, NASA Ames Research Center, 1998.
[38] Muscettola N. HSTS: Integrating planning and scheduling. In Fox, M, and Zweben, M, Eds, Intelligent Scheduling, Morgan Kaufman, 1994.
[39] 李平. ESA 的星上自主验证计划(PROBA).飞行器测控学报,2000,3: 52-60.
[40] Chien S, Knight R, Stechert A, et al. Using Iterative Repair to Improve Responsiveness of Planning and Scheduling. In Proceedings of the Fifth International Conference on Artificial Intelligence Planning and Scheduling, Breckenridge, CO, April 2000.
[41] Pell B, Bernard D, Chien S, et al. A remote agent prototype for spacecraft autonomy. In Proceedings of the SPIE Conference on Optical Science, Engineering and Instrumentation, 1996.
[42] Cichy B, Chien S, Schaffer S. Validating the EO-1 Autonomous Science Agent. International Workshop on Planning and Scheduling for Space, Darmstadt, Germany, June 2004.
[43] Teston F, Creasey R. PROBA:ESA’s Autonomy and Technology Demonstration Mission. In 48th Interntional Astronatical Congress, Turin, 1997.
[44] 代树武.成像侦察卫星调度问题研究.国防科技大学博士学位论文.2004.
[45] 刘洋.航天侦察多星多地面站任务规划问题研究.国防科技大学博士学位论文.2005.
[46] Karia Sycara, Steven F Roth, Norman Sadeh, et a1. Distributed Constrained Heuristic Search. IEEE Transactions on Systems, Man and Cybernetics, 1991, 21(6): 1446-1461.
[47] Grace Yuh-jiun Lin, James J Solberg. Integrated Shop Floor Control Using Autonomous Agents.IIE Transactions, 1992, 24(3): 57-71.
[48] 刘伟,金雁.基于合同网的作业车间分布式合作调度策略.上海交通大学学报,1992,26(2): 77-82.
[49] Reid G Smith. The Contract-Net Protocol: High Level Communication and Control for a Distributed Problem Solver. IEEE Trans Computers, 1980, 29(12): 1104-1113.
[50] Klaus Fischer. Knowledge-based Reactive Scheduling in a Flexible Manufacturing System. IFIP Transactions B: Computer Applications in Technology, 1993(B-15): 1-18.
[51] Carlos Ramos. An Architecture and a Negotiation Protocol for the Dynamic Scheduling of Manufacturing Systems. Proceedings- IEEE International Conference on Robotics and Automation. IEEE, 1994, 3161-3166.
[52] Carlos Ramos. Task Negotiation for Distributed manufacturing System. Proceedings of the IEEE International Symposium on Assembly and Task Planning. IEEE, 1995, 259-264.
[53] Carla P Gomes, Austin Tate, Lyn Thomas. Distributed Scheduling Framework. Proceedings of the International Conference on Tools with Artificial Intelligence. IEEE, 1996, 3849-3850.
[54] Koji Morikawa, Takeshi Furuhashi, Yoshiki Uchikawa. Evolution of CIM System with Genetic Algorithm. IEEE Conference on Evolutionary Computation-Proceedings (2). IEEE, 1994, 746-749.
[55] Rachel Lau, Joel Favrel. Intelligent Scheduling Agent for Distributed Decision-making. Proceedings of the IEEE Conference on Decision and Control(4). IEEE, 1996, 3849-3850.
[56] Kap Hwan Kim, Jong Wook Bae, Joon Yub Song, et al. Distributed Scheduling and Shop Floor Control Method. Computers & Industrial engineering, 1996, 31(3-4): 583-586.
[57] Kap Hwan Kim, Jun Yeob Song, Ki Hong Wang. Negotiation Based Scheduling for Items with Flexible Process Plans. Computers & Industrial Engineering, 1997, 31(3-4): 785-788.
[58] Kouiss K, Pierreval H, Mebarki N. Using Multi-agent Architecture in FMS for Dynamic Scheduling. Journal of Intelligent Manufacturing, 1997, 8(1): 41-47.
[59] F P Maturana, D H Norrie. Multi-Agent Mediator Architecture for Distributed Manufacturing. Journal of Intelligent Manufacturing, 1996, 7(4): 257-270.
[60] A L Ananda, G S H Tan, L F Lau. Distributed Scheduling Algorithms for the Astra Virtual machine. Australian Computer Science Communications, 1997,19(1): 218-227.
[61] Albert D Baker. Survey of Factory Control Algorithms That can be Implemented in a Muti-Agent Heterachy: Dispatching, Scheduling, and Pull. Journal of Manufacturing Systems, 1998,17(4): 297-320.
[62] Siddhartha Bhattacharyya, Gary J Koehler. Learning by Objectives for Adaptive Shop-floor Scheduling. Decision Science, 1998, 29(2): 347-375.
[63] P C Pendharkar. A Computational Study on Design and Performance Issues of Multi-Agent Intelligent Systems for Dynamic Scheduling Enviroments. Expert Systems with Application, 1999(16): 121-133.
[64] Yu Lian, Ohsato Ario, Kawakami Terujyu, et al. CORBA-based Design and Development of Distributed Scheduling Systems: an Application to Flexible Flow Shop Scheduling Systems. Proceedings of the IEEE International Conference on SMC (4). IEEE(SMC); SCJ; SICE; RSJ; JSME IEEE, 1999:IV-522-IV -527.
[65] Knotts Gary, Dror Moshe, Hartman Bruce C. Agent-based Project Scheduling. IIE Transactions, 2000, 32(5): 387-401.
[66] 赵博.结构化集成调度系统理论及基于该理论的虚拟车间智能支撑平台的体系结构研究.大连:大连理工大学,2000.
[67] Chen Y Y, Fu L C, Chen Y C. Multi-agent Based Dynamic Scheduling for a Flexible Assembly System. Proceedings-IEEE International Conference on Robotics and Automation (3). IEEE, 1998, 2122-2127.
[68] Ouelhadj D, Hanachi C, Bouzouia B. Multi-agent System for Dynamic Scheduling and Control in Manufacturing Cells. IEEE International Conference on Robotics and Automation (3). IEEE, 1998, 2128-2133.
[69] Ouelhadj D, Hanachi C, Bouzouia B, et al. Multi-Contract Net Protocol for Dynamic Scheduling in Flexible Manufacturing Systems (FMS). Proceedings- IEEE International Conference on Robotics and Automation (3). IEEE, 1999, 1114-1119.
[70] R J Rabelo, L M Camarinha-matoe. Multi-Agent-Based Agile Scheduling. Robotics and Autonomous Systems, 1999, 27(1):15-28.
[71] 王艳红,尹朝万,张宇.基于多代理和规则调度的敏捷调度系统研究.计算机集成制造系统,2000,6(4): 45—49.
[72] A Brun, A Portioli. Agent-based Shop-Floor Scheduling of Multi Stage Systems. Cpmputers and Industrial Engineering, 1998, 37(1): 457-460.
[73] Weiming Shen, Douglas H Norrie. Dynamic Manufacturing Scheduling Using Both Functional and Resource Related Agents. Intergrated Comuter-Aided Engineering, 2001, 8(1):17-30.
[74] Nils J.Nilsson. Artificial Intelligence: A New Synthesis. China Machine Press. 2000, 361-400.
[75] Stuart Russell, Peter Norvig. Artificial Intelligence: A Modern Approach (Second Edition). Beijing: Posts & Telecom Press, 2004.
[76] 冯健翔.广义人工智能基础研究.北京:宇航出版社,1999.
[77] Fikes R E, Nilsson N J. STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving. In Artificial Intelligence, Vol No 3-4, pp189-208.
[78] M FoxD Long. PDDL2.1: An Extension to PDDL for Expressing Temporal Planning Domains. Unpublished manuscript, 2001.
[79] A Barrett, D Weld. Partial Order Planning: Evaluating Possibleeciency Gains. Articial Intelligence, 1994, 67(1):71-112.
[80] A Gerevini, L Schubert. Accelerating Partial-Order Planners: Some Techniques for Effective Search Control and Pruning. Articial Intelligence Research, 1996, 5: 95-137.
[81] R Kambhampati, A Mali, B Srivastava. Hybrid Planning for Partially Hierarchical Domains. In Proc. 15th Nat. Conf. AI, 1998.
[82] Blum A, Furst M. Fast Planning through Planning Graph Analysis. In Proc.14thInt. Joint Conf. AI, 1995.
[83] Kautz H., McAllester D, Selman B. Encoding Plans in Propositional Logic. In Proc. 5th Int. Conf. Principles of Knowledge Representation and Reasoning, 1996.
[84] D McDermott. Using Regression Graphs to Control Search in Planning. Artificial Intelligence, 1999, 109(1-2):111–160.
[85] J Hoffmann. Extending FF to Numerical State Variables. The Proceedings of the 15th European Conference on Artificial Intelligence, Lyon, France, July 2002.
[86] Malte Helmert. Complexity Results for Standard Benchmark Domains in Planning. Artificial Intelligence, accepted.
[87] D E Smith, J Frank, A K Jonsson. Bridging the Gap between Planning and Scheduling. Knowledge Engineering Review, 15(1), 2000.
[88] J. Walton, Models for the Management of Satellite-based Sensors, Ph.D. Dissertation, Massachusetts Institute of Technology, 1993.
[89] 文 沃 根 . 高 分 辨 率 IKONOS 卫星影像 及 其产品的 特性 . 遥 感 信息 . 2001.1:37-38.
[90] Gordon Petrie. Monitoring Iraq – Imagery Options for Monitoring and Gathering Intelligence. GI News. 2003,1-2.
[91] M. Lema?tre, G. Verfaillie, Selecting and Scheduling Observations of Agile Satellites, Aerospace Science and Technology. 6 (2002) 367-381.
[92] Philippe Baptiste, W P M Nuijten. Constraint Based Scheduling: Applying Constraint Programming to Scheduling Problems. Kluwer Academic Press, 2001
[93] Bartak R.On the Boundary of Planning and Scheduling: a Study. Proceedings of the Eighteenth Workshop of the UK Planning and Scheduling Special Interest Group, Manchester, UK, 1999.
[94] Fikes R E, Nilsson N J. STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving. In Artificial Intelligence, Vol No 3-4, pp189-208.
[95] Allen J, Hendler J, Tate A. Readings in Planning. Morgan Kaufmann, 1990.
[96] Allen J. towards a General Theory of Action and Time. Artificial Intelligence, 1984, 23(2), 123-154.
[97] 杨祥林,诸波,徐宁等.空间光通信技术.南京邮电学院学,2002,3:25-31.
[98] 蔡燕民,陈刚,董作人.空间激光通信系统进展.激光与光电子学进展,2000,5:1-6.
[99] Analytical Graphics Inc. Satellite Tool Kit 5.0. 2003.
[100] 杨颖,王琦.STK 在计算机仿真中的应用.北京:国防工业出版社,2005.
[101] 魏青,薛国宇.微小卫星液化气推进技术.上海航天,2003,5:46-49.
[102] J McCarthy, P J Hayes. Some Philosophical Problems from the Standpoint of Artificial Intelligence. In B. Meltzer and D Michie, editors, Machine Intelligence 4. Edinburgh University Press, 1969.
[103] Minsky M. The Society of Mind. New York: Simon & Schuster, 1986.
[104] Wooldridge M, Jennings N. Intelligent Agents: Theory and Practice. The Knowledge Engineering Review, 1995, 10(2): 115-152.
[105] Mare H Debugging. Multi-Agent System. Information and Software Technology, 1995, 37(2): 102-112.
[106] Hewitt C. A Universal Modular Actor Formalism for AI. In Proceedings of the 3rd International Joint Conference on Artificial Intelligence (IJCAJ-73), 1973: 235-245.
[107] 张洁,高亮,李培根.多 Agent 技术在先进制造中的应用.北京:科学出版社,2004.
[108] Shohan Y. Agent Oriented Programming. Artificial Intelligence, 1993, (60): 51-92.
[109] Brooks R A. Intelligence without Representation. Artificial Intelligence, 1991, 47:139-159.
[110] Jennings N R et al. Agent-based Business Process Man Agent, Int. Journal of Cooperative Information System, 1996, 5(2-3):105-130.
[111] Sycara K P, Wooldridge M. Agents’98: Proceedings of the Second International Conference on Autonomous Agent, ACM Press, 1998.
[112] Rao A S, Georgeff M P. Formal Models and Decision Procedures for Multi-Agent System. Technical Note 61, Australian AI Institute, Level 6, 171 La Trobe Stree, Melbourne, Australia, 1995.
[113] Bratman M E. Intention, Plans and Practical Reason. Harvard University Press, Cabridge, MA.
[114] Jennings N R. Specification and Implementation of Belief Joint-Intention Architecture for Collaborative Problem Solving. Journal of Intelligent and Cooperative Information Systems, 1993, 2(3): 289-318.
[115] Ingrand F F, Georgeff M P, Rao S. An Architecture for Real-Time Reasoning and System Control. IEEE Expert, 1992, 7(6).
[116] 史忠植.高级人工智能.北京:科学出版社,1998.
[117] Minsky M, Riecken D. A Conversation with Marvin Minsky about Agent. Communication of the ACM, 1994, 37(7):23-29.
[118] Muller J P, Wooldridge M, Jennings N R. Intelligent Agent, Ⅲ, LNAI Volume 1193. Springer, Berlin, 1996.
[119] Gerhard Weiss. Multiagent Systems. The MIT Press, 2000.
[120] Simon H A. Models of Bounded Rationality. Cambridge, Mass. MIT Press, 1982-1997,1-3.
[121] Minsky M. The Society of Mind. New York: Simon & Schuster, 1985.
[122] 雷鸣.智能加工监测及知识协同处理的研究.华中理工大学博士论文,1997.
[123] Jennings N R, Sycara K, Wooldridge M. A Roadmap of Agent Research and Development. Autonomous Agents and Muti-Agent Systems, 1998, 10(2):199-215.
[124] 何炎祥.Agent 和多 Agent 系统的设计与应用.武汉:武汉大学出版社,2001.
[125] 张云勇.移动 agent 技术.北京:清华大学出版社,2003.
[126] Lesser V, Decker K, Wanger T. Evolution of the GPGP/TAEMS Domain-independent Coordination Framework. Autonomous Agents and Multi-Agent Systems, 2004(9): 87-143.
[127] Genesereth M R, Ketchet S P. Software Agents. Communication of the ACM, 1993,37(7): 48-53.
[128] Gaines B R, Norrie D H, Lapsley A Z. An Intelligent Information System Supporting the Virtual Manufacturing Enterprise. Proceedings of 1995 IEEE International Conference on Systems, Man and Cybernetics. Vancouver, 1995, 10.
[129] Thomas Schetter, Mark Campbell, Derek Surka. Multiple Agent-based Autonomy for Satellite Constellations. Artificial Intelligence, 2003, 145:147-180.
[130] Pell B, D E Bernard, S A Chien, et al. An Autonomous Spacecraft Agent Prototype. Autonomous Robots, 5(1), 1998.
[131] Ari K Jonsson, Paul H Morris, Nicola Muscettola, et al. Planning in interplanetary space: Theory and practice. In Proceedings of the Fifth International Conference on Artificial Intelligence Planning and Scheduling, 2000.
[132] M Lemaitre, G. Verfaillie, F. Jouhaud, J. Lachiver, and N. Bataille. How to manage the new generation of agile earth observation satellites? In Proceedings of the International Symposium on Artificial Intelligence, Robotics and Automation in Space, 2000.
[133] J. Pemberton. Towards scheduling over-constrained remote sensing satellites. In Proceedings of the 2d InternationalWorkshop on Planning and Scheduling for Space, 2000.
[134] W. Wolfe and S. Sorensen. Three scheduling algorithms applied to the earth observing domain. Management Science, 46(1), 2000.
[135] J C Pemberton, L G Greenwald. On the Need for Dynamic Scheduling of Imaging Satellite. International symposium on Future Intelligent Earth Observing Satellites, 2002.
[136] Reid G Smith. Framework for Distributed Problem Solving. SAE Preprints, Int Jt Conf on Artif Intell (2), 1979:836-841.
[137] Saad A, Kawamura K, Johnson M E et al. Evaluating a Contract Net-based Heterachical Scheduling Approach for Flexible Manufacturing. IEEE International Symposium on Assembly and Task Planning (ISATP’95), Pittsburgh, Pennsylvania, 1995.
[138] Saad A, Salama A, Kawamura K et al. A Bidirectional Contract Net for Production Planning and Scheduling. Proceedings of the UC/IAMS Workshop formanufacturing Research, Cincinnati, Ohio, 1994.
[139] 李道亮,傅泽田,田东.智能系统:基础方法及其在农业中的应用.北京清华大学出版社,2004.
[140] M W P Savelsbergh. The Vehicle Routing Problem with Time Windows: Minimizing Route Duration. INFORMS Journal on Computing, 1992, 4(2):146-154.
[141] Rojanasoonthon, Siwate. Parallel Machine Scheduling With Time Windows. PH.D, University of Texas at Austin, 2004.
[142] 贺仁杰.成像侦察卫星调度问题研究.国防科技大学博士学位论文.2004.
[143] 李菊芳.航天侦察多星多地面站任务规划问题研究.国防科技大学博士学位论文.2005.
[144] 刘洋.成像侦察卫星动态重调度模型、算法及应用研究.国防科技大学博士学位论文.2005.
[145] Erol K, Hendler J, and Nau D. HTN Planning: Complexity and Expressivity. To appear in Proc. AAAI-94, 1994.
[146] 谷长兴,冯志勇.基于 HTN 的供应链优化策略.计算机应用,2003,23(10):103～105.
[147] D Nau, H. Muoz-Avila, Y. Cao, et al. Total-Order Planning with Partially Ordered Subtasks. IJCAI-2001, Seattle, August, 2001.
[148] 范玉顺,曹军威.多代理系统理论、方法与应用.北京:清华大学出版社,2002.
[149] 朱彦伟,杨乐平,陈钦.基于多 Agent 技术的卫星星座设计分析.系统仿真学报,2004,9:2006-2008.
[150] Fabio Bellifemine, Giovanni Caire, Tiziana Trucco. JADE Programmer’s Guide. TILAB, 2005.
[151] Fabio Bellifemine, Giovanni Caire, Tiziana Trucco. JADE Administrator’s Guide. TILAB, 2005.
[152] Foundation for Intelligent Physical Agents. FIPA00023, FIPA Agent Management Specification[ EB /OL ]. http://www.fipa.org/specs/fipa00023/, 2002.
[153] 刘路,斯蒂芬 麦京.小卫星与国际灾害监测星座.中国航天,2004,6:18-21.
[154] 李伯林,左烨. dmc+4 小卫星在国际灾害监测中的应用与评价.遥感学报,2005,4:468-473.
[155] 林来兴.发展我国小卫星星座和测控技术.飞行器测控学报,2000,3:17-22.
[156] 汤君友,杨桂山,赵锐.HT-1 微小卫星及其在国土资源调查中的应用.航天返回与遥感,2003,3:42-46.
[157] 尤政,戴汩.”航天清华一号”微小卫星及其图像处理.遥感学报,2001,3:176-182.
[158] 钱曾波,刘静宇,肖国超.航天摄影测量.北京:解放军出版社,1992:23-40.