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Recurrent Model Predictive Control
This paper proposes an off-line algorithm, called Recurrent Model Predic...
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Mixed Policy Gradient
Reinforcement learning (RL) has great potential in sequential decision-m...
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Separated Proportional-Integral Lagrangian for Chance Constrained Reinforcement Learning
Safety is essential for reinforcement learning (RL) applied in real-worl...
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Ternary Policy Iteration Algorithm for Nonlinear Robust Control
The uncertainties in plant dynamics remain a challenge for nonlinear con...
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Safe Reinforcement Learning for Autonomous Vehicles through Parallel Constrained Policy Optimization
Reinforcement learning (RL) is attracting increasing interests in autono...
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Improving Generalization of Reinforcement Learning with Minimax Distributional Soft Actor-Critic
Reinforcement learning (RL) has achieved remarkable performance in a var...
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Addressing Value Estimation Errors in Reinforcement Learning with a State-Action Return Distribution Function
In current reinforcement learning (RL) methods, function approximation e...
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Direct and indirect reinforcement learning
Reinforcement learning (RL) algorithms have been successfully applied to...
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Deep adaptive dynamic programming for nonaffine nonlinear optimal control problem with state constraints
This paper presents a constrained deep adaptive dynamic programming (CDA...
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Generalized Policy Iteration for Optimal Control in Continuous Time
This paper proposes the Deep Generalized Policy Iteration (DGPI) algorit...
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