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2018 Index IEEE Transactions on Control of Network Systems Vol. 5

2018 IEEE Transactions on Control of Network Systems  
., +, TCNS March 2018 629-639 Minimum-Rank Dynamic Output Consensus Design for Heterogeneous Nonlinear Multi-Agent Systems.  ...  Liu, S., +, TCNS March 2018 167-178 Minimum-Rank Dynamic Output Consensus Design for Heterogeneous Nonlinear Multi-Agent Systems.  ... 
doi:10.1109/tcns.2019.2896050 fatcat:gwrx5cntwrfdzaodscu5jvrdhe

Table of Contents

2020 IEEE Transactions on Network Science and Engineering  
Peng, and G.Chen 3042 Finite-Time Fuzzy Adaptive Consensus for Heterogeneous Nonlinear Multi-Agent Systems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ...  Thai 3100 Distributed Adaptive Fault-Tolerant Consensus of Nonlinear Multi-Agent Systems via State-Constraint Impulsive Protocols With Time-Delay. . . . . . . . . . . . . . . . . . . . . . . . . . . .  ... 
doi:10.1109/tnse.2020.3028672 fatcat:g2rcdwq7zvde5bgpmys3ppvgli

2014 Index IEEE Transactions on Automatic Control Vol. 59

2014 IEEE Transactions on Automatic Control  
., TAC May 2014 1360-1366 1935 Continuous time systems A Mean Square Consensus Protocol for Linear Multi-Agent Systems With Communication Noises and Fixed Topologies.  ...  ., +, TAC Jan. 2014 273-279 Differentially Private Filtering.  ... 
doi:10.1109/tac.2014.2382720 fatcat:jah5kqkafvejrd7xpvyikmi53e

2019 Index IEEE Transactions on Control of Network Systems Vol. 6

2019 IEEE Transactions on Control of Network Systems  
., +, TCNS Dec. 2019 1415-1425 Scheduled-Asynchronous Distributed Algorithm for Optimal Power Flow. Differentially Private Consensus With an Event-Triggered Mechanism.  ...  ., +, TCNS March 2019 388-402 Differentially Private Consensus With an Event-Triggered Mechanism.  ... 
doi:10.1109/tcns.2020.2967203 fatcat:y7saxrrnzvgxjmzz2vrl62ranu

Proximal minimization based distributed convex optimization

Kostas Margellos, Alessandro Falsone, Simone Garatti, Maria Prandini
2016 2016 American Control Conference (ACC)  
We provide a novel iterative algorithm for distributed convex optimization over time-varying multi-agent networks, in the presence of heterogeneous agent constraints.  ...  The main objective of this cooperative set-up is for agents to reach consensus and agree on a common decision that optimizes a certain performance criterion for the overall multi-agent system.  ...  CONCLUSION In this paper we provided a novel algorithm for distributed convex optimization over time-varying multi-agent networks, in the presence of heterogeneous agent constraints.  ... 
doi:10.1109/acc.2016.7525287 dblp:conf/amcc/MargellosFGP16 fatcat:mg5qnaesvreabndv6zipitqnoa

Multi-Level Opinion Dynamics under Bounded Confidence

Gang Kou, Yiyi Zhao, Yi Peng, Yong Shi, Petter Holme
2012 PLoS ONE  
In the literature, agents were generally assumed to have a homogeneous confidence level. This paper proposes an extended model for a group of agents with heterogeneous confidence levels.  ...  Second, a multi-level heterogeneous opinion formation model is formulated under the framework of bounded confidence.  ...  Finally, the 200 agents easily reach consensus as time goes when e~0:245 (Figure 1c).  ... 
doi:10.1371/journal.pone.0043507 pmid:23028458 pmcid:PMC3446962 fatcat:vygkeiwcmrhilh4rfbzoh3srq4

2018 Index IEEE Transactions on Automatic Control Vol. 63

2018 IEEE Transactions on Automatic Control  
., +, TAC Feb. 2018 498-504 Distributed Consensus Algorithms for a Class of High-Order Multi-Agent Systems on Directed Graphs.  ...  Yu, X., +, TAC Aug. 2018 2730-2737 Distributed Consensus Algorithms for a Class of High-Order Multi-Agent Systems on Directed Graphs.  ... 
doi:10.1109/tac.2019.2896796 fatcat:bwmqasulnzbwhin5hv4547ypfe

Fixed-time Distributed Optimization: Consistent Discretization, Time-Varying Topology and Non-Convex Functions [article]

Kunal Garg, Mayank Baranwal, Alfred O. Hero, Dimitra Panagou
2021 arXiv   pre-print
This paper presents a fixed-time convergent and distributed optimization algorithm for first-order multi-agent systems over a time-varying communication topology.  ...  The proposed optimization algorithm combines a fixed-time convergent distributed parameter estimation scheme with a fixed-time distributed consensus scheme as its solution methodology.  ...  Then for the time-varying topology scenario defined by χ (t), Theorem 1 continues to hold even if communication topology switches among Θ for the multi-agent system described in (4) .  ... 
arXiv:1905.10472v4 fatcat:imyb6ow5jnfxjnv7uczuxdgxzi

Privacy-Preserving Communication-Efficient Federated Multi-Armed Bandits [article]

Tan Li, Linqi Song
2021 arXiv   pre-print
To be specific, we design privacy-preserving learning algorithms and communication protocols and derive the learning regret when networked private agents are performing online bandit learning in a master-worker  ...  Our bandit learning algorithms are based on epoch-wise sub-optimal arm eliminations at each agent and agents exchange learning knowledge with the server/each other at the end of each epoch.  ...  Christina Fragouli from UCLA for her valuable discussions and comments when we were conducting this work. We also thank Guangfeng Yan for his insightful discussion for the theoretical proofs.  ... 
arXiv:2111.01570v1 fatcat:jlhrcr53n5d3pejnof7oz6ggwq

Coded Stochastic ADMM for Decentralized Consensus Optimization with Edge Computing [article]

Hao Chen, Yu Ye, Ming Xiao, Mikael Skoglund, H. Vincent Poor
2020 arXiv   pre-print
We consider the problem of learning model parameters in a multi-agent system with data locally processed via distributed edge nodes.  ...  Big data, including applications with high security requirements, are often collected and stored on multiple heterogeneous devices, such as mobile devices, drones and vehicles.  ...  The multi-agent system seeks to find out the optimal solution * by solving (1) . D is the private dataset, which is collected from sensors such as drones and will be allocated into dispersed ECNs.  ... 
arXiv:2010.00914v1 fatcat:o7oy4w4hznehtok35l546kard4

Optimal Output Consensus for Nonlinear Multi-agent Systems with Both Static and Dynamic Uncertainties [article]

Yutao Tang, Xinghu Wang
2020 arXiv   pre-print
In this technical note, we investigate an optimal output consensus problem for heterogeneous uncertain nonlinear multi-agent systems.  ...  The considered agents are described by high-order nonlinear dynamics subject to both static and dynamic uncertainties.  ...  However, optimal output consensus for more general nonlinear multi-agent systems is still far from being solved, especially for agents being heterogeneous and subject to uncertainties.  ... 
arXiv:2001.00715v1 fatcat:j7ki6gg6xnaj7njw47at7gsdda

Blockchain for Multi-Robot Collaboration to Combat COVID-19 and Future Pandemics [article]

S. H. Alsamhi, Brian Lee
2020 arXiv   pre-print
systems.  ...  For combating COVID-19, many heterogeneous and homogenous robots are required to perform different tasks for supporting different purposes in the quarantine area.  ...  Figure. 17 Algorithm of multi-robot collaboration for hospital E2E delivery system VII.  ... 
arXiv:2010.02137v1 fatcat:pyvp7e7zlvbqthejxss5cuccyq

A subgradient based algorithm for distributed task assignment for heterogeneous mobile robots

Alessandro Settimi, Lucia Pallottino
2013 52nd IEEE Conference on Decision and Control  
Moreover, the dynamics of the robot and a private cost function to be optimized together with the assignment are also taken into account.  ...  In this paper the problem of assigning tasks to a set of mobile and heterogeneous robots based on their ability and their costs to accomplish a task is considered.  ...  In such cases an assignment that will be in some sense optimal for the multi-robot system as a whole must be found.  ... 
doi:10.1109/cdc.2013.6760447 dblp:conf/cdc/SettimiP13 fatcat:rqx6rzatanblpeblqwbh45t4ei

Blockchain for Multi-Robot Collaboration to Combat COVID-19 and Future Pandemics

S. H. Alsamhi, Brian Lee, Y Qiao
2020 IEEE Access  
systems.  ...  For combating COVID-19, many heterogeneous and homogenous robots are required to perform different tasks for supporting different purposes in the quarantine area.  ...  FIGURE 15 . 15 Algorithm of multi-robot collaboration for quarantine E2E delivery system.  ... 
doi:10.1109/access.2020.3032450 pmid:34786312 pmcid:PMC8545252 fatcat:coxaihtphzcl3kmobx7pvn4suy

Decentralized Multi-Agent Reinforcement Learning with Networked Agents: Recent Advances [article]

Kaiqing Zhang, Zhuoran Yang, Tamer Başar
2019 arXiv   pre-print
Multi-agent reinforcement learning (MARL) has long been a significant and everlasting research topic in both machine learning and control.  ...  With the recent development of (single-agent) deep RL, there is a resurgence of interests in developing new MARL algorithms, especially those that are backed by theoretical analysis.  ...  samples private to each agent.  ... 
arXiv:1912.03821v1 fatcat:555igege7balrb3iiavbkcj3dy
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