Relevant bibliographies by topics / Discrete Consensus

Academic literature on the topic 'Discrete Consensus'

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Published: 11 March 2023

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Journal articles on the topic "Discrete Consensus"

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Malinowska, Agnieszka B., Ewa Schmeidel, and Małgorzata Zdanowicz. "Discrete leader-following consensus." Mathematical Methods in the Applied Sciences 40, no. 18 (August 11, 2017): 7307–15. http://dx.doi.org/10.1002/mma.4530.

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Chen, Yao, and Jinhu Lü. "Delay-induced discrete-time consensus." Automatica 85 (November 2017): 356–61. http://dx.doi.org/10.1016/j.automatica.2017.07.059.

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Zhu, Minghui, and Sonia Martínez. "Discrete-time dynamic average consensus." Automatica 46, no. 2 (February 2010): 322–29. http://dx.doi.org/10.1016/j.automatica.2009.10.021.

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Montijano, Eduardo, Juan Ignacio Montijano, Carlos Sagüés, and Sonia Martínez. "Robust discrete time dynamic average consensus." Automatica 50, no. 12 (December 2014): 3131–38. http://dx.doi.org/10.1016/j.automatica.2014.10.005.

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Wang, Xiaoping, and Jinliang Shao. "H∞Consensus for Discrete-Time Multiagent Systems." Discrete Dynamics in Nature and Society 2015 (2015): 1–6. http://dx.doi.org/10.1155/2015/380184.

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AnH∞consensus problem of multiagent systems is studied by introducing disturbances into the systems. Based onH∞control theory and consensus theory, a condition is derived to guarantee the systems both reach consensus and have a certainH∞property. Finally, an example is worked out to demonstrate the effectiveness of the theoretical results.
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Kregel, Jan. "The discrete charm of the Washington consensus." Journal of Post Keynesian Economics 30, no. 4 (July 1, 2008): 541–60. http://dx.doi.org/10.2753/pke0160-3477300403.

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Trpevski, I., A. Stanoev, A. Koseska, and L. Kocarev. "Discrete-time distributed consensus on multiplex networks." New Journal of Physics 16, no. 11 (November 26, 2014): 113063. http://dx.doi.org/10.1088/1367-2630/16/11/113063.

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Almeida, João, Carlos Silvestre, and António M. Pascoal. "Continuous-time consensus with discrete-time communications." Systems & Control Letters 61, no. 7 (July 2012): 788–96. http://dx.doi.org/10.1016/j.sysconle.2012.04.004.

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Shih, Chih-Wen, and Jui-Pin Tseng. "Global consensus for discrete-time competitive systems." Chaos, Solitons & Fractals 41, no. 1 (July 2009): 302–10. http://dx.doi.org/10.1016/j.chaos.2007.12.005.

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Jia, Xiao, Laihong Hu, Fujun Feng, and Jun Xu. "Robust H∞ Consensus Control for Linear Discrete-Time Swarm Systems with Parameter Uncertainties and Time-Varying Delays." International Journal of Aerospace Engineering 2019 (July 24, 2019): 1–16. http://dx.doi.org/10.1155/2019/7278531.

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Robust H∞ consensus control problems of linear swarm systems with parameter uncertainties and time-varying delays are investigated. In this literature, a linear consensus protocol for high-order discrete-time swarm systems is proposed. Firstly, the robust H∞ consensus control problem of discrete-time swarm systems is transformed into a robust H∞ control problem of a set of independent uncertain systems. Secondly, sufficient linear matrix inequality conditions for robust H∞ consensus analysis of discrete-time swarm systems are given by the stability theory, and a H∞ performance level γ is determined meanwhile. Thirdly, the convergence result is derived as a final consensus value of swarm systems. Finally, numerical examples are presented to demonstrate theoretical results.
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Dissertations / Theses on the topic "Discrete Consensus"

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FRANCESCHELLI, MAURO. "Consensus Algorithms for Estimation and Discrete Averaging in Networked Control Systems." Doctoral thesis, Università degli Studi di Cagliari, 2011. http://hdl.handle.net/11584/266297.

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In this thesis several topics on consensus and gossip algorithms for multi-agent systems are addressed. An agent is a dynamical system that can be fully described by a state-space representation of its dynamics. A multi-agent system is a network of agents whose pattern of interactions or couplings is described by a graph. Consensus problems in multi-agent systems consist in the study of local interaction rules between the agents such that as global emergent behavior the network converges to the so called "consensus" or "agreement" state where the value of each agent's state is the same and it is possibly a function of the initial network state, for instance the average. A consensus algorithm is thus a set of local interaction rules that solve the consensus problem under some assumptions on the network topology. A gossip algorithm is a set of local state update rules between the agents that, disregarding their objective, are supposed to be implemented in a totally asynchronous way between pairs of neighboring agents, thus resembling the act of "gossiping" in a crowd of people. In this thesis several algorithms based on gossip that solve the consensus and other related problems are presented. In the �first part, several solutions to the consensus problem based on gossip under different sets of assumptions are proposed. In the fi�rst case, it is assumed that the state of the agents is discretized and represents a collection of tasks of different size. In the second case, under the same discretization assumptions of the �rst case, it is assumed that the network is represented by a Hamiltonian graph and it is shown how under this assumption the convergence speed can be improved. In the third case, a solution for the consensus problem for networks represented by arbitrary strongly connected directed graphs is proposed, assuming that the state of the agents is a real number. In the fourth case, a coordinate-free consensus algorithm based on gossip is designed and applied to a network of vehicles able to sense the relative distance between each other but with no access to absolute position information or to a common coordinate system. The proposed algorithm is then used to build in a decentralized way a common reference frame for the network of vehicles. In the second part, a novel local interaction rule based on the consensus equation is proposed together with an algorithm to estimate in a decentralized way the spectrum of the Laplacian matrix that encodes the network topology. As emergent behavior, each agent's state oscillates only at frequencies corresponding to the eigenvalues of the Laplacian matrix thus mapping the spectrum estimation problem into a signal processing problem solvable using the Fourier Transform. It is further shown that the constant component of the emergent behavior in the frequency domain solves the consensus on the average problem. The spectrum estimation algorithm is then applied to leader-follower networks of mobile vehicles to infer in a decentralized way properties such as controllability, osservability and other topological features of the network such as its topology. Finally, a fault detection and recovery technique for sensor networks based on the so called motion-probes is presented to address the inherent lack of robustness against outlier agents in networks implementing consensus algorithms to solve the distributed averaging problem.
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Pedroncelli, Giovanni. "Distributed Discrete Consensus Algorithms: Theory and Applications for the Task Assignment Problem." Doctoral thesis, Università degli studi di Trieste, 2015. http://hdl.handle.net/10077/10975.

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2013/2014
Distributed computation paradigms belong to a research field of increasing interest. Using these algorithms will allow to exploit the capabilities of large scale networks and systems in the near future. Relevant information for the resolution of a problem are distributed among a network of agents with limited memory and computation capability; the problem is solved only by means of local computation and message exchange between neighbour agents. In this thesis we consider the multi-agent assignment problem dealt with distributed computation: a network of agents has to cooperatively negotiate the assignment of a number of tasks by applying a distributed discrete consensus algorithm which defines how the agents exchange information. Consensus algorithms are dealt with always more frequently in the related scientific literature. Therefore, in the first chapter of this thesis we present a related literature review containing some of the most interesting works concerning distributed computation and, in particular, distributed consensus algorithms: some of these works deal with the theory of consensus algorithms, in particular convergence properties, others deal with applications of these algorithms. In the second chapter the main contribution of this thesis is presented: aniterative distributed discrete consensus algorithm based on the resolution of local linear integer optimization problems (L-ILPs) to be used for the multi-agent assignment problem. The algorithm is characterized by theorems proving convergence to a final solution and the value of the convergence time expressed in terms of number of iterations. The chapter is concluded by a performance analysis by means of the results of simulations performed with Matlab software. All the results are presented considering two different network topologies in order to model two different real life scenarios for the connection among agents. The third chapter presents an interesting application of the proposed algorithm: a network of charging stations (considered as agents) has to reach a consensus on the assignment of a number of Electric Vehicles (EVs) requiring to be recharged. In this application the algorithm proposed in the previous chapter undergoes several modifications in order to model effectively this case: considering the inter-arrival times of vehicles to a charging station, a non-linear element appears in the objective function and therefore a novel algorithm to be performed before the assignment algorithm is presented; this algorithm defines the order in which the assigned vehicles have to reach a charging station. Moreover, a communication protocol is proposed by which charging stations and vehicles can communicate and exchange information also allowing charging stations to send to each assigned vehicle the maximum waiting time which can pass before a vehicle loses its right to be recharged. The chapter ends with an example of application of the rivisited assignment algorithm. In the fourth and last chapter, we present an application in an industrial environment: a network of Autonomous Guided Vehicles (AGVs) in a warehouse modeled as a graph has to perform the distributed discrete consensus algorithm in order to assign themselves a set of destinations in which some tasks are located. This application deals not only with the task assignment problem but also with the following destination reaching problem: therefore a distributed coordination algorithm is proposed which allows the AGVs to move into the warehouse avoiding collisions and deadlock. An example of the control strategy application involving both the assignment and coordination algorithms concludes this chapter.
XXVII Ciclo
1986
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Saberian, Aminmohammad. "Applying adjacency based control to distribution networks." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/126755/1/Aminmohammad_Saberian_Thesis.pdf.

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Due to environmental concerns, there is a trend to be less dependent on fossil fuels. This is leading to an increased usage of distributed energy resources in power systems. For the control of distribution networks, an idea has recently been proposed, that shows promising features for several control problems in distribution. This research project demonstrates the adjacency algorithm, including the communication structure for implementing consensus where each agent exchanges information with its immediate neighbours. The adjacency algorithm is demonstrated for three applications; namely voltage control, frequency control using battery reserve energy and the implementation of market clearing for distribution prosumers.
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Ricciardi, Celsi Lorenzo. "Commande non linéaire multi-agents : applications aux systèmes en réseau." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS017/document.

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L'objectif de cette thèse de doctorat est (i) d'étudier et de développer des méthodes d’analyse et de commande de systèmes de contrôle en réseau linéaires et non linéaires et (ii) de montrer le potentiel de ces approches dans des applications complexes pertinentes. À cet égard, la théorie des systèmes à plusieurs agents, la théorie des graphes algébriques et le consensus sont des outils méthodologiques les plus intéressants. Une attention particulière est accordée à la caractérisation des relations entre, d'une part, la topologie du graphe de communication qui sous-tend l'évolution du système à plusieurs agents considéré et, d'autre part, les propriétés spectrales de la matrice Laplacienne associée au graphe lui-même. Le contrôle d'un groupe d'agents autonomes est étudié sous différents angles. Le principal objectif de contrôle est de s’assurer que les agents travaillent ensemble de manière coopérative, où la coopération représente la relation étroite entre tous les agents de l'équipe, le partage de l'information jouant un rôle important. En particulier, beaucoup de problèmes de consensus/accord/ synchronisation /rendez-vous sont étudiés afin de guider un groupe d’agents vers un état commun. Le consensus est étudié dans un contexte à temps discret parce que la dynamique du système est en général continue alors que les mesures et les entrées de contrôle sont des données échantillonnées. En outre, la théorie des jeux est utilisée pour faire face aux problèmes de coordination distribués à plusieurs agents, avec une application aux réseaux connus sous le nom de Software Defined Networks. À cet égard, on peut montrer que, sous des protocoles correctement conçus, les joueurs convergent vers un équilibre unique de Wardrop. On concentre l’attention sur le contrôle distribué, car cette approche présente des avantages évidents par rapport à la centralisation, comme l'évolutivité et la robustesse. Pourtant, le contrôle distribué a également ses propres inconvénients : avant tout, un inconvénient est que chaque agent ne peut pas prédire efficacement le comportement global du groupe en se basant uniquement sur des informations locales. Une certaine attention est également accordée à la nécessité de sécuriser les réseaux électriques contre le danger des attaques cyber-physiques grâce au développement de technologies d'intelligence distribuée. À cet égard, sur la base de topologies de réseaux d'énergie réalistes, nous présentons brièvement la conception d'un schéma de protection contre les attaques dynamiques à un point et à points multiples en boucle fermée. Nous formulons et résolvons un problème d'optimisation non convexe soumis à une contrainte de stabilité de Lyapunov pour la représentation à plusieurs agents autonome d'un réseau électrique obtenue après la linéarisation et l'application des lois d’attaque et de contrôle de fréquence. Finalement, nous présentons des résultats obtenus sur : le pilotage exact de la dynamique non linéaire finie à données échantillonnées avec des retards sur les entrées, au sujet de la stabilisation à données échantillonnées et de la poursuite de l'orbite quasi-halo autour du point de libration translunaire L₂, et au sujet des algorithmes heuristiques basés sur des méthodes d'apprentissage par renforcement à plusieurs agents capables d'effectuer un contrôle adaptatif optimal de qualité de service / qualité de l’expérience dans des scénarios sans modèle
The objective of this PhD thesis is (i) to investigate and develop methods for the analysis and design of linear and nonlinear networked control systems and (ii) to show the potential of such approaches in relevant complex applications. In this respect, multi-agent systems theory, algebraic graph theory and consensus are the most interesting methodological tools, and specific attention is paid to the characterization of the relationships between, on the one hand, the topology of the communication graph that underlies the evolution of the considered multiagent system and, on the other hand, the spectral properties of the Laplacian matrix associated with the graph itself. The control of a group of autonomous agents is investigated from different perspectives. The main control objective is to make sure that the agents work together in a cooperative fashion, where cooperation accounts for the close relationship among all agents in the team, with information sharing playing an important role. In particular, various problems regarding consensus/agreement/synchronization/rendezvous are investigated with the specific aim of driving a group of agents to some common state. Consensus is investigated in a discrete-time setting due to the fact that the system dynamics is normally continuous while the measurements and control inputs might only be made in a sampled-data setting. Moreover, game theory is relied upon in order to cope with distributed multi-agent coordination problems, with application to Software Defined Networks. In this respect, it can be shown that, under properly designed protocols, the players converge to a unique Wardrop equilibrium. We focus on distributed control, since this approach shows obvious benefits over centralization, such as scalability and robustness. Yet, it also has its own drawbacks: among all, one drawback is that each agent cannot effectively predict the overall group behaviour based on only local information. Some attention is also devoted to the need for securing power grids against the danger of cyber-physical attacks through the development of distributed intelligence technologies accompanied by appropriate security enforcements. In this respect, based on realistic power network topologies, we briefly present the design of a protection scheme against closed-loop single-point and multi-point dynamic load altering attacks. This is done by formulating and solving a non-convex optimization problem subject to a Lyapunov stability constraint for the autonomous multiagent representation of a power system obtained after linearization and application of the attack and frequency control laws. Eventually, we show some other results achieved in terms of the exact steeering of finite sampled nonlinear dynamics with input delays, of sampled-data stabilization and quasi-halo orbit following around the L₂ translunar libration point, and of heuristic algorithms based on multi-agent reinforcement learning methods capable of performing optimal adaptive Quality of Service/Quality of Experience control in model-free scenarios
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Ajwad, Syed Ali. "Distributed control of multi-agent systems under communication constraints : application to robotics." Thesis, Poitiers, 2020. http://www.theses.fr/2020POIT2264.

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Les Systèmes Multi-Agents (SMA) ont gagné en popularité en raison de leur vaste gamme d'applications. Les SMA sont utilisés pour atteindre des objectifs complexes qui ne pourraient être atteints par un seul agent. La communication et l'échange d'informations entre les agents d'un SMA sont essentiels pour contrôler son comportement coopératif. Les agents partagent leurs informations avec leurs voisins pour atteindre un objectif commun, ils n'ont donc pas besoin d'unité centrale de surveillance. Cependant, la communication entre les agents est soumise à diverses contraintes pratiques. Ces contraintes incluent des périodes d'échantillonnage irrégulières et asynchrones et la disponibilité d'états partiels uniquement. Ces contraintes posent des défis théoriques et pratiques importants. Dans cette thèse, nous étudions deux problèmes fondamentaux liés au contrôle coopératif distribué, à savoir le consensus et le contrôle de formation pour un SMA à double intégrateur sous ces contraintes. On considère que chaque agent du réseau ne peut mesurer et transmettre son état de position qu'à des instants d'échantillonnage non uniformes et asynchrones. De plus, la vitesse et l'accélération ne sont pas disponibles. Dans un premier temps, nous étudions le problème du contrôle distribué du suivi de consensus. Un algorithme de suivi de leader basé sur l'observateur à temps discret continu est proposé. L'observateur estime la position et la vitesse de l'agent et de son voisin en temps continu à partir des données de position échantillonnées disponibles. Ces états estimés sont ensuite utilisés pour le calcul de l'entrée de commande. Les scénarios de topologie fixe et de topologie commutée sont discutés. Deuxièmement, un protocole de suivi de formation distribué basé sur le consensus est conçu pour réaliser des modèles de formation fixes et variant dans le temps. Le problème d'évitement de collision est également étudié dans cette thèse. Un mécanisme d'évitement de collision basé sur la fonction de potentiel artificiel (APF) est incorporé à l'algorithme de suivi de formation pour empêcher les collisions entre les agents tout en convergeant vers la position souhaitée. Enfin, les algorithmes proposés sont appliqués sur un réseau multi-robots, composé de robots à entraînement différentiel utilisant Robot Operating System (ROS). Un nouveau schéma est proposé pour faire face aux contraintes non holonomiques du robot. L'efficacité des algorithmes sont démontrées à la fois par des résultats de simulation et des expérimentations
Multi-agent systems (MAS) have gained much popularity due to their vast range of applications. MAS is deployed to achieve more complex goals which could not be realized by a single agent alone. Communication and information exchange among the agents in a MAS is crucial to control its cooperative behavior. Agents share their information with their neighbors to reach a common objective, thus do not require any central monitoring unit. However, the communication among the agents is subject to various practical constraints. These constraints include irregular and asynchronous sampling periods and the availability of partial states only. Such constraints pose significant theoretical and practical challenges. In this thesis, we investigate two fundamental problems related to distributed cooperative control, namely consensus and formation control, of double-integrator MAS under these constraints. It is considered that each agent in the network can measure and transmit its position state only at nonuniform and asynchronous sampling instants. Moreover, the velocity and acceleration are not available. First, we study the problem of distributed control of leader-following consensus. A continuous-discrete time observer based leader-following algorithm is proposed. The observer estimates the position and velocity of the agent and its neighbor in continuous time from the available sampled position data. Then these estimated states are used for the computation of the control input. Both fixed and switching topology scenarios are discussed. Secondly, a consensus based distributed formation tracking protocol is designed to achieve both fixed and time-varying formation patterns. Collision avoidance problem is also studied in this thesis. An Artificial Potential Function (APF) based collision avoidance mechanism is incorporated with the formation tracking algorithm to prevent collisions between the agents while converging to a desired position. Finally, the proposed algorithms are applied on a multi-robot network, consisting of differential drive robots using Robot Operating System (ROS). A new scheme is proposed to deal with nonholonomic constraints of the robot. Efficiency of the designed algorithms and their effectiveness in real world applications are shown through both simulation and hardware results
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Tseng, Jui-Pin, and 曾睿彬. "Global Consensus for Discrete-time Competitive System." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/29666934989014479945.

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碩士
國立交通大學
應用數學系所
93
A discrete-time competitive system is studied. We are interested in how the dynamics of the system reach global consensus. Analytical arguments are developed to conclude that every orbit converges to a point as time tends to infinity, without knowing a Lyapunov function.
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RICCIARDI, CELSI LORENZO. "Commande non linéaire multi-agents : applications aux systèmes en réseau (nonlinear multi-agent control with application to networked systems)." Doctoral thesis, 2018. http://hdl.handle.net/11573/1065175.

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The objective of this PhD thesis is (i) to investigate and develop methods for the analysis and design of linear and nonlinear networked control systems and (ii) to show the potential of such approaches in relevant complex applications. In this respect, multi-agent systems theory, algebraic graph theory and consensus are the most interesting methodological tools, and specific attention is paid to the characterization of the relationships between, on the one hand, the topology of the communication graph that underlies the evolution of the considered multi-agent system and, on the other hand, the spectral properties of the Laplacian matrix associated with the graph itself. The control of a group of autonomous agents is investigated from different perspectives. The main control objective is to make sure that the agents work together in a cooperative fashion, where cooperation accounts for the close relationship among all agents in the team, with information sharing playing an important role. In particular, various problems regarding consensus/agreement/synchronization/rendezvous are investigated with the specific aim of driving a group of agents to some common state. Consensus is investigated in a discrete-time setting due to the fact that the system dynamics is normally continuous while the measurements and control inputs might only be made in a sampled-data setting. Moreover, game theory is relied upon in order to cope with distributed multi-agent coordination problems, with application to Software Defined Networks. In this respect, it can be shown that, under properly designed protocols, the players converge to a unique Wardrop equilibrium. We focus on distributed control, since this approach shows obvious benefits over centralization, such as scalability and robustness. Yet, it also has its own drawbacks: among all, one drawback is that each agent cannot effectively predict the overall group behaviour based on only local information. Some attention is also devoted to the need for securing power grids against the danger of cyber-physical attacks through the development of distributed intelligence technologies accompanied by appropriate security enforcements. In this respect, based on realistic power network topologies, we briefly present the design of a protection scheme against closed-loop single-point and multi-point dynamic load altering attacks. This is done by formulating and solving a non-convex optimization problem subject to a Lyapunov stability constraint for the autonomous multi-agent representation of a power system obtained after linearization and application of the attack and frequency control laws. Eventually, we show some other results achieved in terms of the exact steeering of finite sampled nonlinear dynamics with input delays, of sampled-data stabilization and quasi-halo orbit following around the L2 translunar libration point, and of heuristic algorithms based on multi-agent reinforcement learning methods capable of performing optimal adaptive Quality of Service/Quality of Experience control in model-free scenarios.
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Books on the topic "Discrete Consensus"

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Hauswald, Rico, and Lara Keuck. Indeterminacy in medical classification: On continuity, uncertainty, and vagueness. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198722373.003.0005.

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This chapter aims to clarify the terminology of and relations between ontological, epistemological, and semantic aspects of indeterminacy in medical classification systems. Although classifications of diseases and mental disorders are often characterized as having blurred boundaries, there is no consensus on what exactly this means. The following clarification may remedy this shortcoming: from an ontological point of view, disease entities are found to be discrete or continuous, depending on whether realisation gaps occur. From an epistemological perspective, the certainty of a classification depends on how controversial the assessment of its validity is throughout contexts and how much different legitimate interests of classification users vary. Finally, as semantic categories, medical classifications can be defined precisely or vaguely. The chapter analyses how the ontological, epistemological, and semantic levels are interrelated and how the proposed terminological clarifications may help to disentangle discussions about the validity of medical classifications.
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Anderson, Greg. Our Athenian Yesterdays. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190886646.003.0002.

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Part One (“Losing Athens in Translation”) begins by introducing the case study, surveying “democratic Athens,” the consensus modern account of the “way of life” (politeia) which the Athenians called demokratia. This account is a conventional historicist construct, one that forces non-modern experiences to comply with a standard modern template of social being. It thus objectifies the polis as a disenchanted, functionally differentiated terrain inhabited by natural, pre-social individuals. Here, experience is neatly compartmentalized into discrete “orders,” “realms” or “fields,” such as the material and the ideational, the natural and the cultural, sacred and secular, public and private, the political, the social, the economic, and the religious. Athenian demokratia is duly historicized as “democracy,” as a specialist political system which bore a family resemblance to the liberal, egalitarian governments of our own time. And order in Athens is then assumed to radiate out from this male-dominated political system over all other societal fields and realms. As the following chapters will show, there are significant problems with this “democratic Athens” account.
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Book chapters on the topic "Discrete Consensus"

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Mahmoud, MagdiSadek, and Bilal J. Karaki. "Scaled-Type Consensus." In Control Design of Multiagent Discrete-Time Systems, 83–125. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90940-6_3.

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Mahmoud, MagdiSadek, and Bilal J. Karaki. "Leader-Following Consensus." In Control Design of Multiagent Discrete-Time Systems, 241–85. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90940-6_7.

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Zhang, Yinyan, and Shuai Li. "High-Order Discrete-Time Consensus." In Machine Behavior Design And Analysis, 21–44. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3231-3_3.

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Zhang, Yinyan, and Shuai Li. "Discrete-Time Biased Min-Consensus." In Machine Behavior Design And Analysis, 73–96. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3231-3_5.

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Valentini, Gabriele. "Discrete Consensus Achievement in Artificial Systems." In Achieving Consensus in Robot Swarms, 9–32. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53609-5_2.

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Zrour, Rita, Gaëlle Largeteau-Skapin, and Eric Andres. "Optimal Consensus Set for Annulus Fitting." In Discrete Geometry for Computer Imagery, 358–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19867-0_30.

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Dou, Quansheng, Zhongzhi Shi, and Yuehao Pan. "Noisy Control About Discrete Liner Consensus Protocol." In Intelligent Information Processing VIII, 235–44. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48390-0_24.

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Deplano, Diego, Mauro Franceschelli, and Alessandro Giua. "Discrete-Time Dynamic Consensus on the Max Value." In Lecture Notes in Control and Information Sciences - Proceedings, 367–83. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-85318-1_22.

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Zhou, Panpan, and Ben M. Chen. "Leader-Following Output Consensus of Discrete-Time Heterogeneous Systems." In Complex Systems: Spanning Control and Computational Cybernetics: Foundations, 73–87. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99776-2_6.

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Patel, Keyurkumar, and Axaykumar Mehta. "Event-Triggered Discrete-Time Higher Order Sliding Mode Protocol for Leader-Following Consensus of Homogeneous DMAS." In Discrete-Time Sliding Mode Protocols for Discrete Multi-Agent System, 97–109. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6311-9_6.

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Conference papers on the topic "Discrete Consensus"

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Casbeer, David W., Randy Beard, and A. Lee Swindlehurst. "Discrete double integrator consensus." In 2008 47th IEEE Conference on Decision and Control. IEEE, 2008. http://dx.doi.org/10.1109/cdc.2008.4739168.

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Zhou, Jing, and Qian Wang. "Distributed discrete-time nonlinear consensus protocols." In 2009 Joint 48th IEEE Conference on Decision and Control (CDC) and 28th Chinese Control Conference (CCC). IEEE, 2009. http://dx.doi.org/10.1109/cdc.2009.5400537.

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Deshmukh, Raj, Cheolhyeon Kwon, and Inseok Hwang. "Optimal discrete-time Kalman Consensus Filter." In 2017 American Control Conference (ACC). IEEE, 2017. http://dx.doi.org/10.23919/acc.2017.7963859.

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Mengjie Zhou, Jianping He, Peng Cheng, and Jiming Chen. "Discrete average consensus with bounded noise." In 2013 IEEE 52nd Annual Conference on Decision and Control (CDC). IEEE, 2013. http://dx.doi.org/10.1109/cdc.2013.6760718.

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Becchetti, L., A. Clementi, E. Natale, F. Pasquale, and L. Trevisan. "Stabilizing Consensus with Many Opinions." In Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2015. http://dx.doi.org/10.1137/1.9781611974331.ch46.

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Ostaszewska, Urszula, Ewa Schmeidel, and Małgorzata Zdanowicz. "Leader-following consensus on discrete time scales." In INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS (ICNAAM 2017). Author(s), 2018. http://dx.doi.org/10.1063/1.5044162.

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Fanti, Maria Pia, Agostino M. Mangini, Giovanni Pedroncelli, and Walter Ukovich. "Discrete consensus for asynchronous distributed task assignment." In 2016 IEEE 55th Conference on Decision and Control (CDC). IEEE, 2016. http://dx.doi.org/10.1109/cdc.2016.7798278.

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Franceschelli, Mauro, and Andrea Gasparri. "Multi-stage discrete time dynamic average consensus." In 2016 IEEE 55th Conference on Decision and Control (CDC). IEEE, 2016. http://dx.doi.org/10.1109/cdc.2016.7798381.

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Xia, Weiguo, Guodong Shi, Ziyang Meng, Ming Cao, and Karl Henrik Johansson. "Balance conditions in discrete-time consensus algorithms." In 2017 IEEE 56th Annual Conference on Decision and Control (CDC). IEEE, 2017. http://dx.doi.org/10.1109/cdc.2017.8263753.

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Fanti, Maria Pia, Mauro Franceschelli, Agostino Marcello Mangini, Giovanni Pedroncelli, and Walter Ukovich. "Discrete consensus in networks with constrained capacity." In 2013 IEEE 52nd Annual Conference on Decision and Control (CDC). IEEE, 2013. http://dx.doi.org/10.1109/cdc.2013.6760177.

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