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Off-Policy Integral Reinforcement Learning Method for Multi-player Non-zero-Sum Games
Studies in Systems, Decision and Control - Adaptive Dynamic Programming: Single and Multiple Controllers
◽
10.1007/978-981-13-1712-5_12
◽
2018
◽
pp. 227-249
Author(s):
Ruizhuo Song
◽
Qinglai Wei
◽
Qing Li
Keyword(s):
Reinforcement Learning
◽
Learning Method
◽
Zero Sum Games
◽
Zero Sum
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References
Reinforcement Learning Algorithms for Uncertain, Dynamic, Zero-Sum Games
2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA)
◽
10.1109/icmla.2018.00015
◽
2018
◽
Cited By ~ 3
Author(s):
Snehasis Mukhopadhyay
◽
Omkar Tilak
◽
Subir Chakrabarti
Keyword(s):
Reinforcement Learning
◽
Learning Algorithms
◽
Zero Sum Games
◽
Zero Sum
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Optimal tracking control for non‐zero‐sum games of linear discrete‐time systems via off‐policy reinforcement learning
Optimal Control Applications and Methods
◽
10.1002/oca.2597
◽
2020
◽
Vol 41
(4)
◽
pp. 1233-1250
Author(s):
Yinlei Wen
◽
Huaguang Zhang
◽
Hanguang Su
◽
He Ren
Keyword(s):
Reinforcement Learning
◽
Discrete Time
◽
Tracking Control
◽
Optimal Tracking
◽
Zero Sum Games
◽
Optimal Tracking Control
◽
Discrete Time Systems
◽
Zero Sum
◽
Time Systems
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Integral reinforcement learning-based online adaptive event-triggered control for non-zero-sum games of partially unknown nonlinear systems
Neurocomputing
◽
10.1016/j.neucom.2019.09.088
◽
2020
◽
Vol 377
◽
pp. 243-255
◽
Cited By ~ 3
Author(s):
Hanguang Su
◽
Huaguang Zhang
◽
Shaoxin Sun
◽
Yuliang Cai
Keyword(s):
Reinforcement Learning
◽
Nonlinear Systems
◽
Zero Sum Games
◽
Zero Sum
◽
Event Triggered
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Neural-network-based synchronous iteration learning method for multi-player zero-sum games
Neurocomputing
◽
10.1016/j.neucom.2017.02.051
◽
2017
◽
Vol 242
◽
pp. 73-82
◽
Cited By ~ 23
Author(s):
Ruizhuo Song
◽
Qinglai Wei
◽
Biao Song
Keyword(s):
Neural Network
◽
Learning Method
◽
Zero Sum Games
◽
Zero Sum
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Integral Reinforcement Learning for Linear Continuous-Time Zero-Sum Games With Completely Unknown Dynamics
IEEE Transactions on Automation Science and Engineering
◽
10.1109/tase.2014.2300532
◽
2014
◽
Vol 11
(3)
◽
pp. 706-714
◽
Cited By ~ 92
Author(s):
Hongliang Li
◽
Derong Liu
◽
Ding Wang
Keyword(s):
Reinforcement Learning
◽
Continuous Time
◽
Zero Sum Games
◽
Time Zero
◽
Zero Sum
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Reinforcement Learning for Average Reward Zero-Sum Games
Learning Theory - Lecture Notes in Computer Science
◽
10.1007/978-3-540-27819-1_4
◽
2004
◽
pp. 49-63
Author(s):
Shie Mannor
Keyword(s):
Reinforcement Learning
◽
Average Reward
◽
Zero Sum Games
◽
Zero Sum
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Event-based Integral Reinforcement Learning Algorithm for Non-zero-sum Games of Partially Unknown Nonlinear Systems
2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)
◽
10.1109/ddcls52934.2021.9455455
◽
2021
◽
Author(s):
Hanguang Su
◽
Huaguang Zhang
◽
Yanhong Luo
◽
Qiuye Sun
Keyword(s):
Reinforcement Learning
◽
Nonlinear Systems
◽
Learning Algorithm
◽
Zero Sum Games
◽
Zero Sum
◽
Event Based
◽
Reinforcement Learning Algorithm
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A novel Z-function-based completely model-free reinforcement learning method to finite-horizon zero-sum game of nonlinear system
Nonlinear Dynamics
◽
10.1007/s11071-021-07049-z
◽
2022
◽
Author(s):
Zhe Chen
◽
Wenqian Xue
◽
Ning Li
◽
Bosen Lian
◽
Frank L. Lewis
Keyword(s):
Reinforcement Learning
◽
Nonlinear System
◽
Finite Horizon
◽
Learning Method
◽
Model Free
◽
Zero Sum
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Cooperative reinforcement learning based on zero-sum games
2008 SICE Annual Conference
◽
10.1109/sice.2008.4655172
◽
2008
◽
Cited By ~ 2
Author(s):
Kao-Shing Hwang
◽
Jeng-Yih Chiou
◽
Tse-Yu Chen
Keyword(s):
Reinforcement Learning
◽
Zero Sum Games
◽
Zero Sum
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Data-Driven Integral Reinforcement Learning for Continuous-Time Non-Zero-Sum Games
IEEE Access
◽
10.1109/access.2019.2923845
◽
2019
◽
Vol 7
◽
pp. 82901-82912
◽
Cited By ~ 5
Author(s):
Yongliang Yang
◽
Liming Wang
◽
Hamidreza Modares
◽
Dawei Ding
◽
Yixin Yin
◽
...
Keyword(s):
Reinforcement Learning
◽
Continuous Time
◽
Data Driven
◽
Zero Sum Games
◽
Zero Sum
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