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The use of organizational selfdesign to coordinate multiagent systemsKamboj, Sachin. January 2010 (has links)
Thesis (Ph.D.)University of Delaware, 2009. / Principal faculty advisor: Keith S. Decker, Dept. of Computer & Information Sciences. Includes bibliographical references.

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A controller operator graph model for cooperative multiagent systemsCarter, Steven Andrew 03 June 2010 (has links)
M.Sc.(Computer Science) / Agent technology has become more common in mainstream applications as it allows systems to perform routine operations without input from human users. The current evolution of the internet and the increasingly distributed nature of commercial interests, such as bidding auctions, personal shopping assistants and corporate management systems, require software in a distributed environment to be capable of acting autonomously. Multiagent systems have emerged to deal with these distributed environments which can range in size from a couple of agents to potentially infinite agents [Vla03, Rus03]. When considering a cooperative multiagent system, it is important for agents to coordinate effectively. Strategic game theory has introduced a means to coordinate by providing social conventions and roles [Vla03]. Both social conventions and roles help simplify the coordination problem between agents when performing coordination actions. An additional simplification of the coordination problem is to utilise coordination graphs. This reduces the number of agents in the environment to consider for a coordination action [Gue02]. Communication in multiagent systems extends the ability of agents to coordinate with one another. It allows the removal of the requirement to determine the state of participating agents by inspection. Instead, an agent could request the state of another agent by utilising a communication action. Communication does require an additional level of management since agents are rarely allowed to communicate freely and the communication language is not always guaranteed to be standard between agents [Cha02, Vla03]. The dissertation covers the background information regarding multiagent systems and focuses on the elements that are unique to these systems, such as coordination, communication and methods to represent knowledge structures in a multiagent system. A model is then proposed as a framework in which scalable populations of agents are able to coordinate when limited knowledge is available about other agents in the environment. The model, which is called the Controller Operator Graph (COG) model, introduces two unique agent types which help coordinate a large population of agents. The unique agents are provided to assist with communication and coordination in the COG model. The COG model is designed to help agents coordinate in a dynamic environment by providing mechanisms to monitor agent population and goal states. The operator agent is responsible for maintaining communication links between agents and provides the ability to monitor a population of agents for the multiagent system. The controller agent is responsible for ensuring that coordination actions are performed between agents which have no prior knowledge of one another. It provides a means to handle a dynamic situation in which the coordination actions can be extended beyond the original requirements. An implementation of the COG model is provided utilising a supply chain scenario which compares increasing agent populations. The COG implementation demonstrates by means of unified modelling language diagrams a method to design and develop the different concepts in the COG model, such as the execution tree, controller agent and operator agent. The implementation demonstrates the strengths of the COG model, which are handling dynamic environments and achieving dynamic goal states for the environment. The implementation also indicates some of the weaknesses in the COG model, such as greedy agent selection by the controller agent, and single points of failure.

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An upgradeable agentbased model to explore nonlinearity and intangibles in peacekeeping operationsLehmann, Wolfgang. 06 1900 (has links)
Peacekeeping operations (PKO) have become a significant challenge to the German Armed Forces. For the development of tactics, techniques, procedures and equipment with combat operations, agentbased models have been developed, used and exploited for many years. Modeling and simulation of PKO, however, is still in a very early stage. This thesis develops an agentbased model to analyze PKO. Unlike many other multiagent systems (MAS), it implements the rules of discrete event simulation. The chosen software architecture makes the model upgradeable and useful for a breadth of future applications. The modelâ s open architecture and the underlying principle of loosely coupled components make it easy to change or enhance the model. The software agentsâ design incorporates individuality, which is characterized by personality factors. Furthermore, the model is datafarmable. Required data inputs into the simulation tool, i.e., PKO scenarios, are formatted utilizing a stateoftheart technology called Extensible Markup Language (XML), which facilitates use of the data in nearly all computer software packages. The model executes multiple runs of multiple scenarios automatically, demonstrating a robust nature. Finally, an exemplary analysis demonstrates datafarming concepts on the effect of personality factor settings on the potential escalation of a PKO scenario. / German Army author.

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Models of argument for deliberative dialogue in complex domainsToniolo, Alice January 2013 (has links)
In dynamic multiagent systems, selfmotivated agents pursuing individual goals may interfere with each other's plans. Agents must, therefore, coordinate their plans to resolve dependencies among them. This drives the need for agents to engage in dialogue to decide what to do in collaboration. Agreeing what to do is a complex activity, however, when agents come to an encounter with different objectives and norm expectations (i.e. societal norms that constrain acceptable behaviour). Argumentationbased models of dialogue support agents in deciding what to do analysing pros/cons for decisions, and enable conflict resolution by revealing structured background information that facilitates the identification of acceptable solutions. Existing models of deliberative dialogue, however, commonly assume that agents have a shared goal, and to date their effectiveness has been shown only through the use of extended examples. In this research, we propose a novel model of argumentation schemes to be integrated in a dialogue for the identification of plan, goal and norm conflicts when agents have individual but interdependent objectives. We empirically evaluate our model within a dynamic system to establish how the information shared with argumentation schemes influence dialogue outcomes. We show that by employing our model of arguments in dialogue, agents achieve more successful agreements. The resolution of conflicts and identification of more feasible interdependent plans is achieved through the sharing of focussed information driven by argumentation schemes. Agents may also consider more important conflicts, or conflicts that cause higher loss of utility if unresolved. We explore the use of strategies for agents to select arguments that are more likely to solve important conflicts.

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Scaling multiagent reinforcement learning /Proper, Scott. January 1900 (has links)
Thesis (Ph. D.)Oregon State University, 2010. / Printout. Includes bibliographical references (leaves 121123). Also available on the World Wide Web.

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LMI conditions for robust consensus of uncertain nonlinear multiagent systemsHan, Dongkun, 韓東昆 January 2014 (has links)
Establishing consensus is a key probleminmultiagent systems (MASs). This thesis proposes a novel methodology based on convex optimization in the form of linear matrix inequalities (LMIs) for establishing consensus in linear and nonlinear MAS in the presence of model uncertainties, i.e., robust consensus.
Firstly, this thesis investigates robust consensus for uncertain MAS with linear dynamics. Specifically, it is supposed that the system is described by a weighted adjacency matrix whose entries are generic polynomial functions of an uncertain vector constrained in a set described by generic polynomial inequalities. For continuoustime dynamics, necessary and sufficient conditions are proposed to ensure the robust firstorder consensus and the robust secondorder consensus, in both cases of positive and nonpositive weighted adjacency matrices. For discretetime dynamics, necessary and sufficient conditions are provided for robust consensus based on the existence of a Lyapunov function polynomially dependent on the uncertainty. In particular, an upper bound on the degree required for achieving necessity is provided. Furthermore, a necessary and sufficient condition is provided for robust consensus with single integrator and nonnegative weighted adjacency matrices based on the zeros of a polynomial. Lastly, it is shown how these conditions can be investigated through convex optimization by exploiting LMIs.
Secondly, local and global consensus are considered in MAS with intrinsic nonlinear dynamics with respect to bounded solutions, like equilibrium points, periodic orbits, and chaotic orbits. For local consensus, a method is proposed based on the transformation of the original system into an uncertain polytopic system and on the use of homogeneous polynomial Lyapunov functions (HPLFs). For global consensus, another method is proposed based on the search for a suitable polynomial Lyapunov function (PLF). In addition, robust local consensus in MAS is considered with timevarying parametric uncertainties constrained in a polytope. Also, by using HPLFs, a new criteria is proposed where the original system is suitably approximated by an uncertain polytopic system. Tractable conditions are hence provided in terms of LMIs. Then, the polytopic consensus margin problem is proposed and investigated via generalized eigenvalue problems (GEVPs).
Lastly, this thesis investigates robust consensus problem of polynomial nonlinear system affected by timevarying uncertainties on topology, i.e., structured uncertain parameters constrained in a boundedrate polytope. Via partial contraction analysis, novel conditions, both for robust exponential consensus and for robust asymptotical consensus, are proposed by using parameterdependent contraction matrices. In addition, for polynomial nonlinear system, this paper introduces a new class of contraction matrix, i.e., homogeneous parameterdependent polynomial contraction matrix (HPDPCM), by which tractable conditions of LMIs are provided via affine space parametrizations. Furthermore, the variant rate margin for robust asymptotical consensus is proposed and investigated via handling generalized eigenvalue problems (GEVPs).
For each section, a set of representative numerical examples are presented to demonstrate the effectiveness of the proposed results. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

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Agent based modeling for supply chain management examining the impact of information sharing /Zhu, Xiaozhou. January 2008 (has links)
Thesis (Ph.D.)Kent State University, 2008. / Title from PDF t.p. (viewed April 16, 2010). Advisor: Marvin Troutt. Keywords: ABM; agent; repast; information sharing. Includes bibliographical references (p. 161179).

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An agentbased cooperative preference modelJayousi, Rashid January 2003 (has links)
No description available.

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Control of multiagent systems by nonlinear techniques.January 2013 (has links)
在过去的十年间，多智能体系统的协作控制问题引起了广泛的关注。为了解决趋同、编队、蜂拥、群聚等多智能体的协作控制问题，许多研究者提出了各种各样的集中式和分布式控制器。但是这些结果大多是针对线性的多智能体系统的，本论文将利用一些非线性技术去研究线性和非线性的多智能体系统的协作控制问题。 / 1. 有领导者的保持连接的群聚问题: 这类问题的研究主要是针对单点积分器和二重积分器的多智能体系统。为了保持网络的原始链接，我们引入了有界的势能函数，基于这样的势能函数，我们提出了非线性的控制器，所以尽管这样的多智能体系统本身是线性的，但闭环系统是非性的。因此我们利用李雅普诺夫定理来分析闭环系统的性能,并进行了大量的仿真实验来衡量我们的控制器的有效性。具体的结果列如下: / 我们首先研究的系统是带领导的单点积分器的多智能体系统，其中领导是由线性自治系统生成。现有的结果只能处理领导者信号是恒定的或者是斜波信号。而我们提出了一个分布式的状态反馈的控制器，不管领导者的信号是阶跃，斜波还是正弦信号，我们提出的这一控制器都能保持整个系统的原始连接，并且同时能实现各个子系统对领导者的渐近跟踪。 / 我们并进一步研究了二重积分器的多智能体系统，而且这样的系统受到外部信号的干扰。领导者的信号和干扰信号可以是阶跃信号，斜波信号以及具有任意振幅和初始相位的正弦信号的组合。受到一些输出调节理论的启发，我们同时提出了分布式的全状态反馈控制器和带有分布式观测器的输出反馈控制器。尽管存在外部干扰信号，这两种控制器都能保持整个系统的初始连接，同时能实现各个子系统对领导者的渐近跟踪的目标。 / 值得注意的是尽管我们研究是多智能体系统的群聚问题，这种技术同时能用来解决其他类似的编队、蜂拥等协作控制问题。 / 2. 非线性多智能体系统的合作输出调节问题: 我们首先明确地提出了什么是非线性多智能体系统的合作输出调节问题。这个问题可以看作是有领导者的趋同问题的一般化。这个非线性多智能体系统包含了一个领导者和各个子系统，其中领导者的信号由一外部线性自治系统产生，而每个子系统是含有不确定参数的非线性系统，并且这些子系统受到外部信号的干扰。首先我们引入分布式的内模，然后通过坐标变换，得到了一个多输入多输出的增广系统，之后我们把非线性多智能体系统的合作输出调节问题转化成了这个增广系统的全局镇定问题，最后一系列标准的假设下，我们提出了一分布式输出反馈控制器解决了镇定问题，从而解决了输出调节问题。具体来说，假设通信图是连接的，如果我们能解决每个子系统的输出调节问题，那我们提出的分布式输出反馈调节器就能解决这个多智能体系统的合作输出调节问题。我们也把提出的这一控制器应用于洛伦兹多智能体系统的合作输出调节问题。 / Over the past decade, the coordinated control problems for multiagent systems have attracted extensive attention. Both centralized and distributed control protocols have been developed to study such multiagent coordinated control problems as consensus, formation, swarming, flocking, rendezvous and so on. However, most papers employ standard linear control techniques. The results are mainly limited to linear multiagent systems. In this thesis, we will study some coordinated control problems of both linear and nonlinear multiagent systems by some advanced nonlinear techniques. / This thesis has mainly studied two problems. / i) The leaderfollowing rendezvous with connectivity preservation. We have studied this problem for both single integrator and double integrator multiagent systems by nonlinear control laws utilizing bounded potential function. Although the model of multiagent system is linear, the closedloop system is nonlinear due to the employment of nonlinear control laws. We have developed a Lyapunovbased method to analyze the performance of the closedloop system, and conducted extensive simulations to evaluate the effectiveness of our control schemes. The specific results are summarized as follows. / We have studied the case where the leader system is a linear autonomous system and the follower system is a multiple singleintegrator system. The existing results can only handle the case where the leader signal is a constant signal or ramp signal and the control law is discontinuous. By introducing an exosystem, we have proposed a distributed state feedback smooth control law. For a class of reference signals such as step, ramp, and sinusoidal signals, our control law is able to maintain the connectivity of the system and, at the same time, achieve asymptotic tracking of all followers to the output of the leader system. / We have also studied a leaderfollowing rendezvous problem for a double integrator multiagent system subject to external disturbances. Both the leader signal and disturbance signal can be a combination of step signal, ramp signal and sinusoidal signal with arbitrary amplitudes and initial phases. Motivated by some techniques in output regulation theory, we have developed both distributed state feedback control protocol and distributed output feedback control protocol which utilizes a distributed observer. Both of our control laws are able to maintain the connectivity of an initially connected communication network, and, at the same time, achieve the objective of the asymptotic tracking of all followers to the leader regardless of external disturbances. / It is noted that even though we have only studied the rendezvous problem, the techniques of this thesis can also be used to handle other similar problems such as formation, flocking, swarming, etc. / ii) Cooperative output regulation problem of nonlinear multiagent systems. We have formulated the cooperative output regulation problem for nonlinear multiagent systems. The problem can be viewed as a generalization of the leaderfollowing consensus/ synchronization problem in that the leader signals are a class of signals generated by an exosystem, each follower subsystem can be subject to a class of external disturbances, and individual follower subsystems and the leader system have different dynamics. We first show that the problem can be converted into the global stabilization problem of a class of multiinput, multioutput nonlinear systems called augmented system via a set of distributed internal models. Then we further show that, under a set of standard assumptions, the augmented system can be globally stabilized by a distributed output feedback control law. We have solved the cooperative output regulation problem of uncertain nonlinear multiagent systems in output feedback form. The main result can be summarized as follows: assuming the communication graph is connected, then the problem can be solved by a distributed output feedback control law if the global robust output regulation problem for each subsystem can be solved by an output feedback control law. We have also applied our approach to solve a leaderfollowing synchronization problem for a group of Lorenz multiagent systems. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Dong, Yi. / Thesis (Ph.D.)Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 102111). / Abstract also in Chinese. / Abstract  p.i / Acknowledgement  p.v / Chapter 1  Introduction  p.1 / Chapter 1.1  Literature Review  p.1 / Chapter 1.1.1  Leaderfollowing rendezvous with connectivity preservation problem  p.3 / Chapter 1.1.2  Cooperative output regulation problem of nonlinear multiagent systems  p.4 / Chapter 1.2  Thesis Contributions  p.4 / Chapter 1.3  Thesis Organization  p.6 / Chapter 2  Fundamentals  p.8 / Chapter 2.1  Review of Graph Theory Notation  p.8 / Chapter 2.2  Review of Linear Output Regulation  p.9 / Chapter 2.2.1  Regulator equations  p.10 / Chapter 2.2.2  Linear feedback control laws  p.11 / Chapter 2.2.3  Barbalat’s Lemma  p.12 / Chapter 2.3  Review of Nonlinear Output Regulation  p.12 / Chapter 2.3.1  From nonlinear output regulation to stabilization  p.13 / Chapter 2.3.2  Construction of internal model  p.15 / Chapter 2.3.3  Some theories  p.17 / Chapter 3  Leaderfollowing Rendezvous with Connectivity Preservation of Singleintegrator Multiagent Systems  p.19 / Chapter 3.1  Introduction  p.19 / Chapter 3.2  Problem Formulation  p.20 / Chapter 3.3  Solvability of Problem  p.22 / Chapter 3.4  Example  p.28 / Chapter 3.5  Conclusion  p.28 / Chapter 4  A Leaderfollowing Rendezvous Problem of Double Integrator Multiagent Systems  p.30 / Chapter 4.1  Introduction  p.30 / Chapter 4.2  Problem Formulation  p.32 / Chapter 4.3  Main Result  p.34 / Chapter 4.4  Illustrative Examples  p.41 / Chapter 4.4.1  Example 1  p.41 / Chapter 4.4.2  Example 2  p.42 / Chapter 4.5  Conclusion  p.43 / Chapter 5  Leaderfollowing Connectivity Preservation Rendezvous of Multiagent Systems Based Only Position Measurements  p.46 / Chapter 5.1  Introduction  p.46 / Chapter 5.2  Problem Formulation  p.47 / Chapter 5.3  Construction of Distributed Controller  p.49 / Chapter 5.4  Example  p.55 / Chapter 5.5  Conclusion  p.58 / Chapter 6  Cooperative Global Robust Output Regulation for Nonlinear Multiagent Systems in Output Feedback Form  p.61 / Chapter 6.1  Introduction  p.61 / Chapter 6.2  Preliminaries  p.63 / Chapter 6.3  Construction of Distributed Controller  p.66 / Chapter 6.4  Application to Lorenz Multiagent Systems  p.69 / Chapter 6.5  Conclusion  p.72 / Chapter 7  Cooperative Global Output Regulation for a Class of Nonlinear Multiagent Systems  p.75 / Chapter 7.1  Introduction  p.75 / Chapter 7.2  Preliminaries  p.77 / Chapter 7.3  Solvability of Problem  p.82 / Chapter 7.4  Application to HyperChaotic Lorenz Multiagent Systems  p.90 / Chapter 7.5  Concluding Remarks  p.97 / Chapter 8  Conclusions and Future Work  p.100 / Chapter 8.1  Conclusions  p.100 / Chapter 8.2  Future Work  p.101 / Bibliography  p.102 / Biography  p.112

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Modeling and solving decentralized supply chain management problems using multiagent system with dynamiccontrol agentsChau, Wanhin, Derek, 鄒允軒 January 2015 (has links)
Managing large scale supply chains are never an easy task. Numerous researches have put emphasis on supply chain modeling and optimization to assist businesses in searching for the best practices so as to endure the extremely competitive business landscape. To some, the paradigm of centralized supply chain management is adequate for solving its strategic and operational problems. Yet with the improper use of authoritative assumptions, the efficiency of the management process is often jeopardized. Furthermore, current researches in decentralized supply chain are mostly focused on dyadic or linear relationship and seldom consider quantitative modeling and analysis with scalability. Recent development in multiagent systems provided a means for such a modeling methodology and hence researches in this area. To enhance model representativeness and computational efficiency, visionbased control models that are able to simulate individual operational and strategic traits are developed. In this research, pyramidal agent alignment is proposed for simulating the managementoperation dimension with regards to decision exercising and bargaining power management. The system offers one thousand supply chain agents that are simulated in a monolayer, multitier network in real time. Stochastic and dynamic behaviors of the network are handled by statistical regression on scenariobased model evaluation. The proposed design enabled grand scale supply chain modeling and optimization that follows a general or custom simulation supported optimization architecture. Network governance problems and dynamic steering problems are considered and solved using genetic algorithm and dynamic programming. The thesis looks into the potential benefits and limitations of the proposed methods in details, and future research directions are discussed. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

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