Actor-Critic Off-Policy Learning for Optimal Control of Multiple-Model Discrete-Time Systems-Reference-Cited by-同舟云学术

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Actor-Critic Off-Policy Learning for Optimal Control of Multiple-Model Discrete-Time Systems

Published:2018-01 Issue:1 Volume:48 Page:29-40
ISSN:2168-2267
Container-title:IEEE Transactions on Cybernetics
language:
Short-container-title:IEEE Trans. Cybern.

Author:

Skach Jan^ORCID,Kiumarsi Bahare,Lewis Frank L.,Straka Ondrej

Funder

NSF

ONR

Czech Ministry of Education, Youth and Sports

Czech Science Foundation

Fulbright Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Human-Computer Interaction,Information Systems,Control and Systems Engineering,Software

Link

http://ieeexplore.ieee.org/ielaam/6221036/8207702/7731150-aam.pdf

Cited by 47 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Neural Adaptive Optimal Control of Inequality-Constrained Nonlinear System With Partial Uncertain Time Delay;IEEE Transactions on Systems, Man, and Cybernetics: Systems;2024-07

2. Optimized Backstepping Combined With Dynamic Surface Technique for Single-Input–Single-Output Nonlinear Strict-Feedback System;IEEE Transactions on Systems, Man, and Cybernetics: Systems;2024-07

3. Robust hierarchical games of linear discrete-time systems based on off-policy model-free reinforcement learning;Journal of the Franklin Institute;2024-05

4. Efficient Reinforcement Learning With the Novel N-Step Method and V-Network;IEEE Transactions on Cybernetics;2024

5. References;Cooperative Control of Multi-Agent Systems with Uncertainties;2024

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