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1
Graph theoretic methods in multiagent networks
Graph theoretic methods in multiagent networks
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Graph theoretic methods in multiagent networks

2010 Princeton University Press ;ISBN: 1400835356 ;ISBN: 9781400835355 ;ISBN: 9780691140612 ;ISBN: 0691140618 ;EISBN: 1400835356 ;EISBN: 9781400835355 ;DOI: 10.1515/9781400835355 ;OCLC: 701703574 ;LCCallNum: T57.85.M43 2010

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2
Distributed Consensus Observer for Multiagent Systems With High-Order Integrator Dynamics
Distributed Consensus Observer for Multiagent Systems With High-Order Integrator Dynamics
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Distributed Consensus Observer for Multiagent Systems With High-Order Integrator Dynamics

IEEE transactions on automatic control, 2020-04, Vol.65 (4), p.1771-1778 [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 0018-9286 ;EISSN: 1558-2523 ;DOI: 10.1109/TAC.2019.2936555

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3
Methods of geomonitoring of technogenic objects to determine fast-flowing deformation processes using robotics
Methods of geomonitoring of technogenic objects to determine fast-flowing deformation processes using robotics
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Methods of geomonitoring of technogenic objects to determine fast-flowing deformation processes using robotics

Journal of physics. Conference series, 2020-11, Vol.1661 (1), p.12115 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;2020. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/1661/1/012115

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4
Negotiable Votes: Pre-Vote Negotiations in Binary Voting with Non-Manipulable Rules
Negotiable Votes: Pre-Vote Negotiations in Binary Voting with Non-Manipulable Rules
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Negotiable Votes: Pre-Vote Negotiations in Binary Voting with Non-Manipulable Rules

The Journal of artificial intelligence research, 2019-04, Vol.64, p.895-929 [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 1076-9757 ;EISSN: 1943-5037 ;DOI: 10.1613/jair.1.11446

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5
Finite-time/fixed-time consensus of multi-agent systems
Finite-time/fixed-time consensus of multi-agent systems
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Finite-time/fixed-time consensus of multi-agent systems

Nanjing Xinxi Gongcheng Daxue Xuebao, 2019-08, Vol.11 (4), p.409-413 [Peer Reviewed Journal]

Copyright Nanjing University of Information Science & Technology 2019 ;ISSN: 1674-7070 ;DOI: 10.13878/j.cnki.jnuist.2019.04.007

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6
Data-Driven Revision of Conditional Norms in Multi-Agent Systems
Data-Driven Revision of Conditional Norms in Multi-Agent Systems
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Data-Driven Revision of Conditional Norms in Multi-Agent Systems

info:eu-repo/semantics/OpenAccess ;ISSN: 1076-9757 ;EISSN: 1943-5037

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7
Distributed Control of Nonlinear Systems With Unknown Time-Varying Control Coefficients: A Novel Nussbaum Function Approach
Distributed Control of Nonlinear Systems With Unknown Time-Varying Control Coefficients: A Novel Nussbaum Function Approach
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Distributed Control of Nonlinear Systems With Unknown Time-Varying Control Coefficients: A Novel Nussbaum Function Approach

IEEE transactions on automatic control, 2023-07, Vol.68 (7), p.4191-4203 [Peer Reviewed Journal]

ISSN: 0018-9286 ;EISSN: 1558-2523 ;DOI: 10.1109/TAC.2022.3206135 ;CODEN: IETAA9

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8
Distributed Constraint Optimization Problems and Applications: A Survey
Distributed Constraint Optimization Problems and Applications: A Survey
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Distributed Constraint Optimization Problems and Applications: A Survey

The Journal of artificial intelligence research, , Vol.61, p.623-698 [Peer Reviewed Journal]

2018. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the associated terms available at https://www.jair.org/index.php/jair/about ;ISSN: 1076-9757 ;EISSN: 1943-5037 ;DOI: 10.1613/jair.5565

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9
Multi-Robot Symmetric Formations for Gradient and Hessian Estimation with Application to Source Seeking
Multi-Robot Symmetric Formations for Gradient and Hessian Estimation with Application to Source Seeking
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Multi-Robot Symmetric Formations for Gradient and Hessian Estimation with Application to Source Seeking

IEEE transactions on robotics, 2019-06, Vol.35 (3), p.782-789 [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 1552-3098 ;EISSN: 1941-0468 ;DOI: 10.1109/TRO.2019.2895509

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10
Observer-Based Consensus of Higher-Order Nonlinear Heterogeneous Multiagent Systems with Unmatched Uncertainties: Application on Robotic Systems
Observer-Based Consensus of Higher-Order Nonlinear Heterogeneous Multiagent Systems with Unmatched Uncertainties: Application on Robotic Systems
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Observer-Based Consensus of Higher-Order Nonlinear Heterogeneous Multiagent Systems with Unmatched Uncertainties: Application on Robotic Systems

Robotica, 2020-09, Vol.38 (9), p.1605-1626 [Peer Reviewed Journal]

Cambridge University Press 2019 ;ISSN: 0263-5747 ;EISSN: 1469-8668 ;DOI: 10.1017/S0263574719001656

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11
A Survey on Transfer Learning for Multiagent Reinforcement Learning Systems
A Survey on Transfer Learning for Multiagent Reinforcement Learning Systems
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A Survey on Transfer Learning for Multiagent Reinforcement Learning Systems

The Journal of artificial intelligence research, 2019-01, Vol.64, p.645-703 [Peer Reviewed Journal]

2019. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the associated terms available at https://www.jair.org/index.php/jair/about ;ISSN: 1076-9757 ;EISSN: 1943-5037 ;DOI: 10.1613/jair.1.11396

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12
Grandmaster level in StarCraft II using multi-agent reinforcement learning
Grandmaster level in StarCraft II using multi-agent reinforcement learning
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Grandmaster level in StarCraft II using multi-agent reinforcement learning

Nature (London), 2019-11, Vol.575 (7782), p.350-354 [Peer Reviewed Journal]

COPYRIGHT 2019 Nature Publishing Group ;COPYRIGHT 2019 Nature Publishing Group ;Copyright Nature Publishing Group Nov 14, 2019 ;ISSN: 0028-0836 ;EISSN: 1476-4687 ;DOI: 10.1038/s41586-019-1724-z ;PMID: 31666705

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13
Multi-agent deep reinforcement learning: a survey
Multi-agent deep reinforcement learning: a survey
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Multi-agent deep reinforcement learning: a survey

The Artificial intelligence review, 2022-02, Vol.55 (2), p.895-943 [Peer Reviewed Journal]

The Author(s) 2021 ;COPYRIGHT 2022 Springer ;The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0269-2821 ;EISSN: 1573-7462 ;DOI: 10.1007/s10462-021-09996-w

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14
Simplicial Activity Driven Model
Simplicial Activity Driven Model
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Simplicial Activity Driven Model

Physical review letters, 2018-11, Vol.121 (22) [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 0031-9007 ;EISSN: 1079-7114 ;DOI: 10.1103/PhysRevLett.121.228301

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15
A Sum-of-States Preservation Framework for Open Multiagent Systems With Nonlinear Heterogeneous Coupling
A Sum-of-States Preservation Framework for Open Multiagent Systems With Nonlinear Heterogeneous Coupling
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A Sum-of-States Preservation Framework for Open Multiagent Systems With Nonlinear Heterogeneous Coupling

IEEE transactions on automatic control, 2024-03, Vol.69 (3), p.1991-1998 [Peer Reviewed Journal]

ISSN: 0018-9286 ;EISSN: 1558-2523 ;DOI: 10.1109/TAC.2023.3317728 ;CODEN: IETAA9

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16
Principles and practice of multi-agent systems
Principles and practice of multi-agent systems
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Principles and practice of multi-agent systems

Knowledge engineering review, 2019, Vol.34, Article e3 [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 0269-8889 ;EISSN: 1469-8005 ;DOI: 10.1017/S0269888918000243

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17
Explainability in Deep Reinforcement Learning
Explainability in Deep Reinforcement Learning
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Explainability in Deep Reinforcement Learning

Knowledge-based systems, 2021-02 [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 0950-7051 ;EISSN: 1872-7409 ;DOI: 10.1016/j.knosys.2020.106685

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18
Set-to-Sequence Methods in Machine Learning: A Review
Set-to-Sequence Methods in Machine Learning: A Review
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Article 		Add to My Research

Set-to-Sequence Methods in Machine Learning: A Review

The Journal of artificial intelligence research, 2021, Vol.71, p.885-924 [Peer Reviewed Journal]

2021. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the associated terms available at https://www.jair.org/index.php/jair/about ;ISSN: 1076-9757 ;EISSN: 1943-5037 ;DOI: 10.1613/jair.1.12839

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19
Distributed Adaptive Time-Varying Group Formation Tracking for Multiagent Systems With Multiple Leaders on Directed Graphs
Distributed Adaptive Time-Varying Group Formation Tracking for Multiagent Systems With Multiple Leaders on Directed Graphs
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Distributed Adaptive Time-Varying Group Formation Tracking for Multiagent Systems With Multiple Leaders on Directed Graphs

IEEE transactions on control of network systems, 2020-03, Vol.7 (1), p.140-150 [Peer Reviewed Journal]

EISSN: 2325-5870 ;DOI: 10.1109/TCNS.2019.2913619 ;CODEN: ITCNAY

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20
Outracing champion Gran Turismo drivers with deep reinforcement learning
Outracing champion Gran Turismo drivers with deep reinforcement learning
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Article 		Add to My Research

Outracing champion Gran Turismo drivers with deep reinforcement learning

Nature (London), 2022-02, Vol.602 (7896), p.223-228 [Peer Reviewed Journal]

2022. The Author(s), under exclusive licence to Springer Nature Limited. ;Copyright Nature Publishing Group Feb 10, 2022 ;ISSN: 0028-0836 ;EISSN: 1476-4687 ;DOI: 10.1038/s41586-021-04357-7 ;PMID: 35140384

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