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Model-free Q-learning designs for linear discrete-time zero-sum games with application to H-infinity control
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Machine learning for securing Cyber–Physical Systems under cyber attacks: A survey
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Policy Iteration Algorithm for the Control of Oxygenation
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Off-Policy Q-Learning for Anti-Interference Control of Multi-Player Systems
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Event-triggered adaptive dynamic programming for discrete-time multi-player games
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Online Nash-optimization tracking control of multi-motor driven load system with simplified RL scheme
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Networked controller and observer design of discrete-time systems with inaccurate model parameters
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Interconnection and damping assignment control based on modified actor–critic algorithm with wavelet function approximation
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Adaptive quantile control for stochastic system
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Finite-horizon optimal secure tracking control under denial-of-service attacks
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Inverse reinforcement learning for discrete-time linear systems based on inverse optimal control
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Multiplayer Pareto optimal control with H∞ constraint for nonlinear stochastic system via online synchronous reinforcement learning
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An integrated data-driven Markov parameters sequence identification and adaptive dynamic programming method to design fault-tolerant optimal tracking control for completely unknown model systems
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Q-learning solution for optimal consensus control of discrete-time multiagent systems using reinforcement learning
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