摘要
智能控制与决策系统的设计与实现是当前人工智能研究领域的热门问题。本文将自组织多Agent系统理论引入到智能控制与决策系统的研究中,在深入研究智能控制与决策系统相关理论及应用的基础上,设计了基于物理激励的多Agent交互模型和基于自组织多Agent系统的智能控制与决策模型,并设计和实现了一个完整的基于物理激励的自组织多Agent智能控制与决策系统平台。主要研究工作内容包括:
1、系统详尽地阐述了自组织理论和多Agent系统理论的基本内容,并针对自组织理论与多Agent系统理论相互结合的问题,即多Agent系统中的自组织行为和自组织多Agent系统进行了阐述。
2、提出一个基于物理激励的多Agent交互模型。该模型的基本原理是以牛顿经典物理学中的万有引力定律为基础,用人工构造的虚拟作用力作为多Agent之间交互行为的基础,通过交互场景的定义、吸引或排斥交互机制的选择、多Agent角色和行为的定义和多Agent交互过程的选择四个步骤完成建模工作。实验结果表明,该模型可以很方便的进行物理实现,并能克服传统的多Agent交互模型理论计算能力不足的缺点,具有较强的通用性和实用性。
3、提出一个基于自组织多Agent系统的智能控制与决策模型及其实现算法范例。该模型由环境和自组织多Agent系统两大部分构成,通过环境的定义、环境的识别、多Agent控制与决策过程以及多Agent控制与决策输出四个基本步骤完成建模工作。该模型可以灵活地选择多种算法进行具体的实现工作,文中给出的实现算法范例在微观上以多Agent之间的交互运算为基础,宏观上以统计物理学对多Agent系统的整体统计运算为核心,充分利用了自组织多Agent系统的群体决策优势。实验结果表明,该模型及其实现算法范例可以很方便的进行物理实现,并且具有很强的灵活性和通用性。
4、提出并实现了一个完整的基于物理激励的自组织多Agent智能控制与决策系统平台。该系统平台的构成是以基于物理激励的多Agent交互子系统和基于自组织多Agent系统的智能控制与决策子系统为核心,同时配以环境识别与输入子系统、控制与决策输出子系统和人机交互子系统实现具体的智能控制与决策功能。实验结果表明,该系统具有较好的有效性、灵活性、鲁棒性和适应性等特点,对于较为复杂的实时控制环境也具有较强的环境适应能力,对于实际环境中的具体应用具有可行性。
5、全文最后进行了总结工作,对后续的研究工作进行了进一步设想,并对该领域的未来研究方向进行了展望。
The design and implementation of an intelligent control and decision making system is currently a hot issue in the field of artificial intelligence research. This dissertation introduces the self-organizing multi-agent system into the research of the intelligent control and decision making system. In this dissertation, studied with the intelligent control and decision making theories and applications, the Physics-Inspired Multi-agent Interaction model and the Intelligent Control and Decision Making Model based on the Self-organizing Multi-agent System are designed. Meanwhile, a complete platform of the Physics-Inspired Self-organizing Multi-agent Intelligent Control and Decision Making System is also designed and implemented. The main contributions of the dissertation are summarized as follows:
1. The basic concepts of self-organization and multi-agent system are illustrated. The presentations of the problem of combining the self-organization theory and multi-agent system theory are also illustrated, i.e. the self-organizing behaviors in the multi-agent system and the self-organizing multi-agent systems.
2. A Physics-Inspired Multi-agent Interaction Model is proposed. The basic principle of this model is based on the classical Newtonian physics - Newton’s law of universal gravitation and the artificially constructed virtual interaction forces among multiple agents. The model is modeling through the following four steps - the definition of interaction scenarios, the choice of attraction or repulsion interaction mechanisms, the definition of multiple agents’roles and behaviors and the choice of the multi-agent interaction process. Experimental results show that this model can be easily implemented and can overcome the shortcoming of insufficient calculating capacity of the traditional multi-agent interaction model with strong versatility and reliability.
3. An Intelligent Control and Decision Making Model based on the Self-organizing Multi-agent System and a paradigm of its implementation algorithms are proposed. This model is consisted of two major components– Environment and Self-organization Multi-agent System. It is modeling by the following four steps - the definition of environment, the identification of environment, the process of multi-agent control and decision making and the output of multi-agent control and decision making. It can be specifically achieved by flexible choosing a variety of algorithms, and the paradigm of its implementation algorithms given in the dissertation is based on the interaction computing among multiple agents in the microscope, while as the core of the overall statistical computing of the multi-agent system by using the statistical physics in the macro scope. The model is full of use the group decision making advantages of the self-organizing multi-agent system. Experimental results show that the model and the paradigm of its implementation algorithms can be easily implemented with great flexibility and versatility.
4. A complete platform of the Physics-Inspired Self-organizing Multi-agent Intelligent Control and Decision Making System is proposed and implemented. In the composition of this system platform, the Physics-Inspired Multi-agent Interaction subsystem and the Intelligent Control and Decision Making subsystem based on the Self-organizing Multi-agent System are as the core components. In order to realize the particular intelligent control and decision making functions, the additional subsystems include the environmental identification and input subsystem, the control and decision making output subsystem and the human-computer interaction subsystem. Experimental results show that this system platform has good validity, flexibility, robustness and adaptability. It also has a strong ability to the complex real-time control environment and the feasibility to the actual environment for specific applications.
5. The summary of the whole text and the ideas of the further research works are given at the end. The prospect of future research directions is also discussed.
引文
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