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Found 2 papers, 2 papers with code
Stable and Safe Human-aligned Reinforcement Learning through Neural Ordinary Differential Equations
Reinforcement learning (RL) excels in applications such as video games, but ensuring safety as well as the ability to achieve the specified goals remains challenging when using RL for real-world problems, such as human-aligned tasks where human safety is paramount.
Stable and Safe Reinforcement Learning via a Barrier-Lyapunov Actor-Critic Approach
Reinforcement learning (RL) has demonstrated impressive performance in various areas such as video games and robotics.
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