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Titlebook: Machine Behavior Design And Analysis; A Consensus Perspect Yinyan Zhang,Shuai Li Book 2020 Springer Nature Singapore Pte Ltd. 2020 distribu

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書目名稱Machine Behavior Design And Analysis
副標(biāo)題A Consensus Perspect
編輯Yinyan Zhang,Shuai Li
視頻videohttp://file.papertrans.cn/621/620341/620341.mp4
概述The first book focusing on min-consensus and relevant issues for multi-agent systems.Includes both theoretical analyses of the models and simulative examples of various consensus protocols.Convenient
圖書封面Titlebook: Machine Behavior Design And Analysis; A Consensus Perspect Yinyan Zhang,Shuai Li Book 2020 Springer Nature Singapore Pte Ltd. 2020 distribu
描述.In this book, we present our systematic investigations into consensus in multi-agent systems. We show the design and analysis of various types of consensus protocols from a multi-agent perspective with a focus on min-consensus and its variants. We also discuss second-order and high-order min-consensus. A very interesting topic regarding the link between consensus and path planning is also included. We show that a biased min-consensus protocol can lead to the path planning phenomenon, which means that the complexity of shortest path planning can emerge from a perturbed version of min-consensus protocol, which as a case study may encourage researchers in the field of distributed control to rethink the nature of complexity and the distance between control and intelligence. We also illustrate the design and analysis of consensus protocols for nonlinear multi-agent systems derived from an optimal control formulation, which do not require solving a Hamilton-Jacobi-Bellman (HJB) equation...The book was written in a self-contained format. For each consensus protocol, the performance is verified through simulative examples and analyzed via mathematical derivations, using tools like graph t
出版日期Book 2020
關(guān)鍵詞distributed computing; distributed control; path planning; machine behavior; multi-agent system
版次1
doihttps://doi.org/10.1007/978-981-15-3231-3
isbn_softcover978-981-15-3233-7
isbn_ebook978-981-15-3231-3
copyrightSpringer Nature Singapore Pte Ltd. 2020
The information of publication is updating

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Discrete-Time Biased Min-Consensus,min-consensus protocol and is convergent in finite time. It should be noted that the protocol here is not obtained by using difference rules to the continuous-time biased min-consensus protocol in the previous chapter, and thus the theoretical analysis is different. The convergence property of the d
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Biased Consensus Based Distributed Neural Network,is described as a linear program with the aid of the optimality principle of dynamic programming. Then, continuous-time recurrent neural networks related to consensus protocols are designed for solve the linear program, in which each node in the shortest path problem is represented by a neuron. It i
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Adaptive Near-Optimal Consensus,re complicated scenario of the problem discussed in the previous chapter. Following the idea in the previous chapter, the problem is described as a dynamic optimization problem, i.e., an optimal control problem, which is reduced into a simpler convex optimization problem via using the Taylor expansi
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Near-Optimal Consensus,he closed-loop system is exponentially asymptotically stable, by which the conclusion about the asymptotic optimality of the consensus protocol is also derived. The effectiveness of the scheme is illustrated via numerical simulations.
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