arXiv Machine Learning
RL-PaO: Prediction as Action in Decision Making under Uncertainty
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Toward an Energy-Optimized Operation of Data Centers Located in Wind Farms Using Reinforcement Learning
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Solving Markov Decision Processes with Future Information via MPC
Model Predictive Control (MPC) is widely used in industrial and robotic systems for enforcing constraints and embedding domain knowledge through finite-horizon optimization-based planning. However, despite these strengths, an MPC scheme typically does not yield optimal policies for sequential decision-making problems formulated as Markov Decision Processes (MDPs).
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Reward-rate Policy Gradient for Efficient Machine Learning Engineering Agents
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