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Kaiqing Zhang
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Books and Theses
- 2021
- [b1]Kaiqing Zhang:
Reinforcement learning for multi-agent and robust control systems. University of Illinois Urbana-Champaign, USA, 2021
Journal Articles
- 2023
- [j16]Bin Hu, Kaiqing Zhang, Na Li, Mehran Mesbahi, Maryam Fazel, Tamer Basar:
Toward a Theoretical Foundation of Policy Optimization for Learning Control Policies. Annu. Rev. Control. Robotics Auton. Syst. 6: 123-158 (2023) - [j15]Kaiqing Zhang, Sham M. Kakade, Tamer Basar, Lin F. Yang:
Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity. J. Mach. Learn. Res. 24: 175:1-175:53 (2023) - [j14]Han Shen
, Kaiqing Zhang, Mingyi Hong
, Tianyi Chen
:
Towards Understanding Asynchronous Advantage Actor-Critic: Convergence and Linear Speedup. IEEE Trans. Signal Process. 71: 2579-2594 (2023) - 2022
- [j13]Xingyu Sha, Jiaqi Zhang, Keyou You, Kaiqing Zhang, Tamer Basar:
Fully asynchronous policy evaluation in distributed reinforcement learning over networks. Autom. 136: 110092 (2022) - [j12]Tianyi Chen
, Kaiqing Zhang
, Georgios B. Giannakis
, Tamer Basar
:
Communication-Efficient Policy Gradient Methods for Distributed Reinforcement Learning. IEEE Trans. Control. Netw. Syst. 9(2): 917-929 (2022) - 2021
- [j11]Kaiqing Zhang
, Zhuoran Yang, Tamer Basar:
Decentralized multi-agent reinforcement learning with networked agents: recent advances. Frontiers Inf. Technol. Electron. Eng. 22(6): 802-814 (2021) - [j10]Xingran Wang, Yiyao Zhang
, Kaiqing Zhang, Yi Yuan:
Influence of behavioral state on the neuromodulatory effect of low-intensity transcranial ultrasound stimulation on hippocampal CA1 in mouse. NeuroImage 241: 118441 (2021) - [j9]Kaiqing Zhang
, Bin Hu, Tamer Basar:
Policy Optimization for ℋ2 Linear Control with ℋ∞ Robustness Guarantee: Implicit Regularization and Global Convergence. SIAM J. Control. Optim. 59(6): 4081-4109 (2021) - [j8]Kaiqing Zhang
, Zhuoran Yang
, Han Liu
, Tong Zhang
, Tamer Basar
:
Finite-Sample Analysis for Decentralized Batch Multiagent Reinforcement Learning With Networked Agents. IEEE Trans. Autom. Control. 66(12): 5925-5940 (2021) - [j7]Yi Yuan
, Kaiqing Zhang, Yiyao Zhang
, Jiaqing Yan, Zhijie Wang, Xingran Wang, Mengyang Liu
, Xiaoli Li
:
The Effect of Low-Intensity Transcranial Ultrasound Stimulation on Neural Oscillation and Hemodynamics in the Mouse Visual Cortex Depends on Anesthesia Level and Ultrasound Intensity. IEEE Trans. Biomed. Eng. 68(5): 1619-1626 (2021) - 2020
- [j6]Kaiqing Zhang, Yang Liu, Ji Liu, Mingyan Liu, Tamer Basar:
Distributed learning of average belief over networks using sequential observations. Autom. 115: 108857 (2020) - [j5]Kaiqing Zhang
, Alec Koppel
, Hao Zhu, Tamer Basar:
Global Convergence of Policy Gradient Methods to (Almost) Locally Optimal Policies. SIAM J. Control. Optim. 58(6): 3586-3612 (2020) - 2019
- [j4]Alec Koppel
, Kaiqing Zhang
, Hao Zhu
, Tamer Basar
:
Projected Stochastic Primal-Dual Method for Constrained Online Learning With Kernels. IEEE Trans. Signal Process. 67(10): 2528-2542 (2019) - 2018
- [j3]Kaiqing Zhang
, Wei Shi, Hao Zhu
, Emiliano Dall'Anese
, Tamer Basar
:
Dynamic Power Distribution System Management With a Locally Connected Communication Network. IEEE J. Sel. Top. Signal Process. 12(4): 673-687 (2018) - 2017
- [j2]Yingchen Zhang, Rui Yang, Kaiqing Zhang, Huaiguang Jiang, Jun Jason Zhang:
Consumption Behavior Analytics-Aided Energy Forecasting and Dispatch. IEEE Intell. Syst. 32(4): 59-63 (2017) - 2015
- [j1]Feifei Gao, Kaiqing Zhang:
Enhanced multi-parameter cognitive architecture for future wireless communications. IEEE Commun. Mag. 53(7): 86-92 (2015)
Conference and Workshop Papers
- 2024
- [c60]Lirui Wang, Kaiqing Zhang, Allan Zhou, Max Simchowitz, Russ Tedrake:
Robot Fleet Learning via Policy Merging. ICLR 2024 - 2023
- [c59]Yiding Chen, Xuezhou Zhang, Kaiqing Zhang, Mengdi Wang, Xiaojin Zhu:
Byzantine-Robust Online and Offline Distributed Reinforcement Learning. AISTATS 2023: 3230-3269 - [c58]Sarath Pattathil, Kaiqing Zhang, Asuman E. Ozdaglar:
Symmetric (Optimistic) Natural Policy Gradient for Multi-Agent Learning with Parameter Convergence. AISTATS 2023: 5641-5685 - [c57]Yi Tian, Kaiqing Zhang, Russ Tedrake, Suvrit Sra:
Toward Understanding State Representation Learning in MuZero: A Case Study in Linear Quadratic Gaussian Control. CDC 2023: 6166-6171 - [c56]Qiwen Cui, Kaiqing Zhang, Simon S. Du:
Breaking the Curse of Multiagents in a Large State Space: RL in Markov Games with Independent Linear Function Approximation. COLT 2023: 2651-2652 - [c55]Max Simchowitz, Abhishek Gupta, Kaiqing Zhang:
Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective. COLT 2023: 3356-3468 - [c54]Constantinos Daskalakis, Noah Golowich, Kaiqing Zhang:
The Complexity of Markov Equilibrium in Stochastic Games. COLT 2023: 4180-4234 - [c53]Mingyang Liu, Asuman E. Ozdaglar, Tiancheng Yu, Kaiqing Zhang:
The Power of Regularization in Solving Extensive-Form Games. ICLR 2023 - [c52]Aviv Netanyahu, Abhishek Gupta, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal:
Learning to Extrapolate: A Transductive Approach. ICLR 2023 - [c51]Lirui Wang, Kaiqing Zhang, Yunzhu Li, Yonglong Tian, Russ Tedrake:
Does Learning from Decentralized Non-IID Unlabeled Data Benefit from Self Supervision? ICLR 2023 - [c50]Xiangyu Liu, Kaiqing Zhang:
Partially Observable Multi-agent RL with (Quasi-)Efficiency: The Blessing of Information Sharing. ICML 2023: 22370-22419 - [c49]Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang:
Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation. ICML 2023: 26769-26791 - [c48]Yi Tian, Kaiqing Zhang, Russ Tedrake, Suvrit Sra:
Can Direct Latent Model Learning Solve Linear Quadratic Gaussian Control? L4DC 2023: 51-63 - [c47]Boyuan Chen, Chuning Zhu, Pulkit Agrawal, Kaiqing Zhang, Abhishek Gupta:
Self-Supervised Reinforcement Learning that Transfers using Random Features. NeurIPS 2023 - [c46]Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman E. Ozdaglar, Adam Wierman:
A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games. NeurIPS 2023 - [c45]Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Alejandro Ribeiro:
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs. NeurIPS 2023 - [c44]Chanwoo Park, Kaiqing Zhang, Asuman E. Ozdaglar:
Multi-Player Zero-Sum Markov Games with Networked Separable Interactions. NeurIPS 2023 - 2022
- [c43]Lujie Yang, Kaiqing Zhang, Alexandre Amice, Yunzhu Li, Russ Tedrake:
Discrete Approximate Information States in Partially Observable Environments. ACC 2022: 1406-1413 - [c42]Dongsheng Ding, Kaiqing Zhang, Tamer Basar, Mihailo R. Jovanovic:
Convergence and optimality of policy gradient primal-dual method for constrained Markov decision processes. ACC 2022: 2851-2856 - [c41]Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Mihailo R. Jovanovic:
Independent Policy Gradient for Large-Scale Markov Potential Games: Sharper Rates, Function Approximation, and Game-Agnostic Convergence. ICML 2022: 5166-5220 - [c40]Weichao Mao, Lin Yang
, Kaiqing Zhang, Tamer Basar:
On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning. ICML 2022: 15007-15049 - [c39]Hyung Ju Suh, Max Simchowitz, Kaiqing Zhang, Russ Tedrake:
Do Differentiable Simulators Give Better Policy Gradients? ICML 2022: 20668-20696 - [c38]Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang:
What is a Good Metric to Study Generalization of Minimax Learners? NeurIPS 2022 - [c37]Jack Umenberger, Max Simchowitz, Juan C. Perdomo, Kaiqing Zhang, Russ Tedrake:
Globally Convergent Policy Search for Output Estimation. NeurIPS 2022 - [c36]Muhammed O. Sayin
, Kaiqing Zhang, Asuman E. Ozdaglar:
Fictitious Play in Markov Games with Single Controller. EC 2022: 919-936 - 2021
- [c35]Songtao Lu, Kaiqing Zhang, Tianyi Chen, Tamer Basar, Lior Horesh:
Decentralized Policy Gradient Descent Ascent for Safe Multi-Agent Reinforcement Learning. AAAI 2021: 8767-8775 - [c34]Zengyi Qin, Kaiqing Zhang, Yuxiao Chen, Jingkai Chen, Chuchu Fan:
Learning Safe Multi-agent Control with Decentralized Neural Barrier Certificates. ICLR 2021 - [c33]Weichao Mao, Kaiqing Zhang, Ruihao Zhu, David Simchi-Levi, Tamer Basar:
Near-Optimal Model-Free Reinforcement Learning in Non-Stationary Episodic MDPs. ICML 2021: 7447-7458 - [c32]Wesley Suttle, Kaiqing Zhang, Zhuoran Yang, Ji Liu, David N. Kraemer:
Reinforcement Learning for Cost-Aware Markov Decision Processes. ICML 2021: 9989-9999 - [c31]Kaiqing Zhang, Xiangyuan Zhang, Bin Hu, Tamer Basar:
Derivative-Free Policy Optimization for Linear Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity. NeurIPS 2021: 2949-2964 - [c30]Muhammed O. Sayin, Kaiqing Zhang, David S. Leslie, Tamer Basar, Asuman E. Ozdaglar:
Decentralized Q-learning in Zero-sum Markov Games. NeurIPS 2021: 18320-18334 - 2020
- [c29]Muhammad Aneeq uz Zaman
, Kaiqing Zhang, Erik Miehling, Tamer Basar:
Approximate Equilibrium Computation for Discrete-Time Linear-Quadratic Mean-Field Games. ACC 2020: 333-339 - [c28]Muhammad Aneeq uz Zaman
, Kaiqing Zhang, Erik Miehling, Tamer Basar:
Reinforcement Learning in Non-Stationary Discrete-Time Linear-Quadratic Mean-Field Games. CDC 2020: 2278-2284 - [c27]Weichao Mao, Kaiqing Zhang, Erik Miehling, Tamer Basar:
Information State Embedding in Partially Observable Cooperative Multi-Agent Reinforcement Learning. CDC 2020: 6124-6131 - [c26]Kaiqing Zhang, Bin Hu, Tamer Basar:
Policy Optimization for H2 Linear Control with H∞ Robustness Guarantee: Implicit Regularization and Global Convergence. L4DC 2020: 179-190 - [c25]Dongsheng Ding, Kaiqing Zhang, Tamer Basar, Mihailo R. Jovanovic:
Natural Policy Gradient Primal-Dual Method for Constrained Markov Decision Processes. NeurIPS 2020 - [c24]Yanli Liu, Kaiqing Zhang, Tamer Basar, Wotao Yin:
An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods. NeurIPS 2020 - [c23]Weichao Mao, Kaiqing Zhang, Qiaomin Xie, Tamer Basar:
POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis. NeurIPS 2020 - [c22]Kaiqing Zhang, Bin Hu, Tamer Basar:
On the Stability and Convergence of Robust Adversarial Reinforcement Learning: A Case Study on Linear Quadratic Systems. NeurIPS 2020 - [c21]Kaiqing Zhang, Sham M. Kakade, Tamer Basar, Lin F. Yang
:
Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity. NeurIPS 2020 - [c20]Kaiqing Zhang, Tao Sun, Yunzhe Tao, Sahika Genc, Sunil Mallya, Tamer Basar:
Robust Multi-Agent Reinforcement Learning with Model Uncertainty. NeurIPS 2020 - 2019
- [c19]Kaiqing Zhang, Erik Miehling, Tamer Basar:
Online Planning for Decentralized Stochastic Control with Partial History Sharing. ACC 2019: 3544-3550 - [c18]Yixuan Lin, Kaiqing Zhang, Zhuoran Yang, Zhaoran Wang, Tamer Basar, Romeil Sandhu, Ji Liu:
A Communication-Efficient Multi-Agent Actor-Critic Algorithm for Distributed Reinforcement Learning. CDC 2019: 5562-5567 - [c17]Kaiqing Zhang, Alec Koppel, Hao Zhu, Tamer Basar:
Convergence and Iteration Complexity of Policy Gradient Method for Infinite-horizon Reinforcement Learning. CDC 2019: 7415-7422 - [c16]Kaiqing Zhang, Alec Koppel, Hao Zhu, Tamer Basar:
Policy Search in Infinite-Horizon Discounted Reinforcement Learning: Advances through Connections to Non-Convex Optimization : Invited Presentation. CISS 2019: 1-3 - [c15]Xiangyuan Zhang, Kaiqing Zhang, Erik Miehling, Tamer Basar:
Non-Cooperative Inverse Reinforcement Learning. NeurIPS 2019: 9482-9493 - [c14]Kaiqing Zhang, Zhuoran Yang, Tamer Basar:
Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games. NeurIPS 2019: 11598-11610 - 2018
- [c13]Kaiqing Zhang, Zhuoran Yang, Zhaoran Wang:
Nonlinear Structured Signal Estimation in High Dimensions via Iterative Hard Thresholding. AISTATS 2018: 258-268 - [c12]Kaiqing Zhang, Wei Shi, Hao Zhu, Tamer Basar:
Distributed Equilibrium-Learning for Power Network Voltage Control With a Locally Connected Communication Network. ACC 2018: 3092-3097 - [c11]Zhuoran Yang, Kaiqing Zhang, Mingyi Hong, Tamer Basar:
A Finite Sample Analysis of the Actor-Critic Algorithm. CDC 2018: 2759-2764 - [c10]Kaiqing Zhang, Zhuoran Yang, Tamer Basar:
Networked Multi-Agent Reinforcement Learning in Continuous Spaces. CDC 2018: 2771-2776 - [c9]Kaiqing Zhang, Hao Zhu, Tamer Basar, Alec Koppel:
Projected Stochastic Primal-Dual Method for Constrained Online Learning with Kernels. CDC 2018: 4224-4231 - [c8]Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar:
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents. ICML 2018: 5867-5876 - 2017
- [c7]Kaiqing Zhang, Hao Zhu:
A game-theoretic approach for communication-free voltage-VAR optimization. GlobalSIP 2017: 1055-1059 - [c6]Kaiqing Zhang, Siming Guo, Hao Zhu:
Parameter Sensitivity and Dependency Analysis for the WECC Dynamic Composite Load Model. HICSS 2017: 1-8 - 2016
- [c5]Kaiqing Zhang, Yuan Shen
, Moe Z. Win
:
On the performance of map-aware cooperative localization. ICC 2016: 1-6 - 2015
- [c4]Lubing Han, Feifei Gao, Kaiqing Zhang, Shun Zhang:
Sequential Detection Aided Modulation Classification in Cognitive Radio Networks. GLOBECOM 2015: 1-6 - [c3]Kaiqing Zhang, Hong Hu, Wenhan Dai, Yuan Shen
, Moe Z. Win
:
An area state-aided indoor localization algorithm and its implementation. ICC Workshops 2015: 736-741 - [c2]Zhao Zhang, Kaiqing Zhang, Feifei Gao, Shun Zhang:
Spectrum prediction and channel selection for sensing-based spectrum sharing scheme using online learning techniques. PIMRC 2015: 355-359 - 2014
- [c1]Kaiqing Zhang, Jiachen Li, Feifei Gao:
Machine learning techniques for spectrum sensing when primary user has multiple transmit powers. ICCS 2014: 137-141
Informal and Other Publications
- 2024
- [i58]Chanwoo Park, Xiangyu Liu, Asuman E. Ozdaglar, Kaiqing Zhang:
Do LLM Agents Have Regret? A Case Study in Online Learning and Games. CoRR abs/2403.16843 (2024) - [i57]Chanwoo Park, Mingyang Liu, Dingwen Kong, Kaiqing Zhang, Asuman E. Ozdaglar:
RLHF from Heterogeneous Feedback via Personalization and Preference Aggregation. CoRR abs/2405.00254 (2024) - 2023
- [i56]Qiwen Cui, Kaiqing Zhang, Simon S. Du:
Breaking the Curse of Multiagents in a Large State Space: RL in Markov Games with Independent Linear Function Approximation. CoRR abs/2302.03673 (2023) - [i55]Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman E. Ozdaglar, Adam Wierman:
A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games. CoRR abs/2303.03100 (2023) - [i54]Aviv Netanyahu, Abhishek Gupta, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal:
Learning to Extrapolate: A Transductive Approach. CoRR abs/2304.14329 (2023) - [i53]Boyuan Chen, Chuning Zhu, Pulkit Agrawal, Kaiqing Zhang, Abhishek Gupta:
Self-Supervised Reinforcement Learning that Transfers using Random Features. CoRR abs/2305.17250 (2023) - [i52]Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Alejandro Ribeiro:
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs. CoRR abs/2306.11700 (2023) - [i51]Max Simchowitz, Abhishek Gupta, Kaiqing Zhang:
Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective. CoRR abs/2307.06457 (2023) - [i50]Chanwoo Park, Kaiqing Zhang, Asuman E. Ozdaglar:
Multi-Player Zero-Sum Markov Games with Networked Separable Interactions. CoRR abs/2307.09470 (2023) - [i49]Xiangyu Liu, Kaiqing Zhang:
Partially Observable Multi-agent RL with (Quasi-)Efficiency: The Blessing of Information Sharing. CoRR abs/2308.08705 (2023) - [i48]Lirui Wang, Kaiqing Zhang, Allan Zhou, Max Simchowitz, Russ Tedrake:
Fleet Policy Learning via Weight Merging and An Application to Robotic Tool-Use. CoRR abs/2310.01362 (2023) - [i47]Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman E. Ozdaglar, Adam Wierman:
Two-Timescale Q-Learning with Function Approximation in Zero-Sum Stochastic Games. CoRR abs/2312.04905 (2023) - 2022
- [i46]H. J. Terry Suh, Max Simchowitz, Kaiqing Zhang, Russ Tedrake:
Do Differentiable Simulators Give Better Policy Gradients? CoRR abs/2202.00817 (2022) - [i45]Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Mihailo R. Jovanovic:
Independent Policy Gradient for Large-Scale Markov Potential Games: Sharper Rates, Function Approximation, and Game-Agnostic Convergence. CoRR abs/2202.04129 (2022) - [i44]Jack Umenberger, Max Simchowitz, Juan C. Perdomo, Kaiqing Zhang, Russ Tedrake:
Globally Convergent Policy Search over Dynamic Filters for Output Estimation. CoRR abs/2202.11659 (2022) - [i43]Constantinos Daskalakis, Noah Golowich, Kaiqing Zhang:
The Complexity of Markov Equilibrium in Stochastic Games. CoRR abs/2204.03991 (2022) - [i42]Muhammed O. Sayin
, Kaiqing Zhang, Asuman E. Ozdaglar:
Fictitious Play in Markov Games with Single Controller. CoRR abs/2205.11389 (2022) - [i41]Yiding Chen, Xuezhou Zhang, Kaiqing Zhang, Mengdi Wang
, Xiaojin Zhu:
Byzantine-Robust Online and Offline Distributed Reinforcement Learning. CoRR abs/2206.00165 (2022) - [i40]Dongsheng Ding, Kaiqing Zhang, Jiali Duan, Tamer Basar, Mihailo R. Jovanovic:
Convergence and sample complexity of natural policy gradient primal-dual methods for constrained MDPs. CoRR abs/2206.02346 (2022) - [i39]Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang:
What is a Good Metric to Study Generalization of Minimax Learners? CoRR abs/2206.04502 (2022) - [i38]Mingyang Liu
, Asuman E. Ozdaglar, Tiancheng Yu, Kaiqing Zhang:
The Power of Regularization in Solving Extensive-Form Games. CoRR abs/2206.09495 (2022) - [i37]Bin Hu, Kaiqing Zhang, Na Li, Mehran Mesbahi, Maryam Fazel, Tamer Basar:
Towards a Theoretical Foundation of Policy Optimization for Learning Control Policies. CoRR abs/2210.04810 (2022) - [i36]Lirui Wang, Kaiqing Zhang, Yunzhu Li, Yonglong Tian, Russ Tedrake:
Does Decentralized Learning with Non-IID Unlabeled Data Benefit from Self Supervision? CoRR abs/2210.10947 (2022) - [i35]Sarath Pattathil, Kaiqing Zhang, Asuman E. Ozdaglar:
Symmetric (Optimistic) Natural Policy Gradient for Multi-agent Learning with Parameter Convergence. CoRR abs/2210.12812 (2022) - [i34]Yanli Liu, Kaiqing Zhang, Tamer Basar, Wotao Yin:
An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods. CoRR abs/2211.07937 (2022) - [i33]Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang:
Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation. CoRR abs/2212.13861 (2022) - [i32]Yi Tian, Kaiqing Zhang, Russ Tedrake, Suvrit Sra:
Can Direct Latent Model Learning Solve Linear Quadratic Gaussian Control? CoRR abs/2212.14511 (2022) - 2021
- [i31]Kaiqing Zhang, Xiangyuan Zhang, Bin Hu, Tamer Basar:
Derivative-Free Policy Optimization for Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity. CoRR abs/2101.01041 (2021) - [i30]Zengyi Qin, Kaiqing Zhang, Yuxiao Chen, Jingkai Chen, Chuchu Fan:
Learning Safe Multi-Agent Control with Decentralized Neural Barrier Certificates. CoRR abs/2101.05436 (2021) - [i29]Muhammed O. Sayin, Kaiqing Zhang, David S. Leslie, Tamer Basar, Asuman E. Ozdaglar:
Decentralized Q-Learning in Zero-sum Markov Games. CoRR abs/2106.02748 (2021) - [i28]Weichao Mao, Tamer Basar, Lin F. Yang, Kaiqing Zhang:
Decentralized Cooperative Multi-Agent Reinforcement Learning with Exploration. CoRR abs/2110.05707 (2021) - [i27]Asuman E. Ozdaglar, Muhammed O. Sayin, Kaiqing Zhang:
Independent Learning in Stochastic Games. CoRR abs/2111.11743 (2021) - 2020
- [i26]Xingyu Sha, Jiaqi Zhang, Kaiqing Zhang, Keyou You, Tamer Basar:
Asynchronous Policy Evaluation in Distributed Reinforcement Learning over Networks. CoRR abs/2003.00433 (2020) - [i25]Muhammad Aneeq uz Zaman, Kaiqing Zhang, Erik Miehling, Tamer Basar:
Approximate Equilibrium Computation for Discrete-Time Linear-Quadratic Mean-Field Games. CoRR abs/2003.13195 (2020) - [i24]Weichao Mao, Kaiqing Zhang, Erik Miehling, Tamer Basar:
Information State Embedding in Partially Observable Cooperative Multi-Agent Reinforcement Learning. CoRR abs/2004.01098 (2020) - [i23]Weichao Mao, Kaiqing Zhang, Qiaomin Xie, Tamer Basar:
POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis. CoRR abs/2006.04672 (2020) - [i22]Kaiqing Zhang, Sham M. Kakade, Tamer Basar, Lin F. Yang:
Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity. CoRR abs/2007.07461 (2020) - [i21]Muhammad Aneeq uz Zaman, Kaiqing Zhang, Erik Miehling, Tamer Basar:
Reinforcement Learning in Non-Stationary Discrete-Time Linear-Quadratic Mean-Field Games. CoRR abs/2009.04350 (2020) - [i20]Weichao Mao, Kaiqing Zhang, Ruihao Zhu, David Simchi-Levi, Tamer Basar:
Near-Optimal Regret Bounds for Model-Free RL in Non-Stationary Episodic MDPs. CoRR abs/2010.03161 (2020) - [i19]Han Shen, Kaiqing Zhang, Mingyi Hong, Tianyi Chen:
Asynchronous Advantage Actor Critic: Non-asymptotic Analysis and Linear Speedup. CoRR abs/2012.15511 (2020) - 2019
- [i18]Wesley Suttle, Zhuoran Yang, Kaiqing Zhang, Zhaoran Wang, Tamer Basar, Ji Liu:
A Multi-Agent Off-Policy Actor-Critic Algorithm for Distributed Reinforcement Learning. CoRR abs/1903.06372 (2019) - [i17]Kaiqing Zhang, Zhuoran Yang, Tamer Basar:
Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games. CoRR abs/1906.00729 (2019) - [i16]Kaiqing Zhang, Alec Koppel, Hao Zhu, Tamer Basar:
Global Convergence of Policy Gradient Methods to (Almost) Locally Optimal Policies. CoRR abs/1906.08383 (2019) - [i15]Yixuan Lin, Kaiqing Zhang, Zhuoran Yang, Zhaoran Wang, Tamer Basar, Romeil Sandhu, Ji Liu:
A Communication-Efficient Multi-Agent Actor-Critic Algorithm for Distributed Reinforcement Learning. CoRR abs/1907.03053 (2019) - [i14]Wesley Suttle, Zhuoran Yang, Kaiqing Zhang, Ji Liu:
Stochastic Convergence Results for Regularized Actor-Critic Methods. CoRR abs/1907.06138 (2019) - [i13]Kaiqing Zhang, Erik Miehling, Tamer Basar:
Online Planning for Decentralized Stochastic Control with Partial History Sharing. CoRR abs/1908.02357 (2019) - [i12]Kaiqing Zhang, Bin Hu, Tamer Basar:
Policy Optimization for H2 Linear Control with H∞ Robustness Guarantee: Implicit Regularization and Global Convergence. CoRR abs/1910.09496 (2019) - [i11]Xiangyuan Zhang, Kaiqing Zhang, Erik Miehling, Tamer Basar:
Non-Cooperative Inverse Reinforcement Learning. CoRR abs/1911.04220 (2019) - [i10]Kaiqing Zhang, Zhuoran Yang, Tamer Basar:
Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms. CoRR abs/1911.10635 (2019) - [i9]Kaiqing Zhang, Zhuoran Yang, Tamer Basar:
Decentralized Multi-Agent Reinforcement Learning with Networked Agents: Recent Advances. CoRR abs/1912.03821 (2019) - 2018
- [i8]Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar:
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents. CoRR abs/1802.08757 (2018) - [i7]Kaiqing Zhang, Wei Shi, Hao Zhu, Tamer Basar:
Distributed Equilibrium-Learning for Power Network Voltage Control With a Locally Connected Communication Network. CoRR abs/1803.10792 (2018) - [i6]Kaiqing Zhang, Wei Shi, Hao Zhu, Emiliano Dall'Anese, Tamer Basar:
Dynamic Power Distribution System Management With a Locally Connected Communication Network. CoRR abs/1803.10804 (2018) - [i5]Kaiqing Zhang, Yang Liu, Ji Liu, Mingyan Liu, Tamer Basar:
Distributed Learning of Average Belief Over Networks Using Sequential Observations. CoRR abs/1811.07799 (2018) - [i4]Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar:
Finite-Sample Analyses for Fully Decentralized Multi-Agent Reinforcement Learning. CoRR abs/1812.02783 (2018) - [i3]Tianyi Chen, Kaiqing Zhang, Georgios B. Giannakis, Tamer Basar:
Communication-Efficient Distributed Reinforcement Learning. CoRR abs/1812.03239 (2018) - 2015
- [i2]Kaiqing Zhang, Hong Hu, Wenhan Dai, Yuan Shen, Moe Z. Win:
Indoor Localization Algorithm For Smartphones. CoRR abs/1503.07628 (2015) - 2014
- [i1]Kaiqing Zhang, Feifei Gao, Qihui Wu:
Enhanced Multi-Parameter Cognitive Architecture for Future Wireless Communications. CoRR abs/1411.6137 (2014)
Coauthor Index
![](https://dblp.uni-trier.de/img/cog.dark.24x24.png)
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