Applying Quantitative Model Checking to Analyze Safety in Reinforcement Learning
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DOI: 10.1109/access.2024.3358408
Abstract: Reinforcement learning (RL) is rapidly used in safety-centric applications. However, many studies focus on generating optimal policy that achieves maximum rewards. While maximum rewards are beneficial, safety constraints and non-functional requirements must also be considered… read more here.
Keywords: maximum rewards; safety constraints; functional requirements; reinforcement learning ... See more keywords