arXiv Machine Learning July 20, 2026 By Marco C. Campi, Simone Garatti

Pick-to-Learn Calibration of an MPC Policy for an Origin-to-Destination Flight Problem

Read the original on arXiv Machine Learning →

arXiv:2607. 16084v1 Announce Type: cross Abstract: This paper illustrates the Pick-to-Learn methodology applied to the calibration of a Model Predictive Control policy.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv Machine Learning

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Wind-Aware Reinforcement Learning Control of a Small Quadrotor Using Learned Onboard Wind Estimation in Simulated Atmospheric Turbulence

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arXiv AI

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Learning from World Feedback: Why Model Uncertainty Fails as a Risk Signal in Model-Based RL

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Anticipatory Reinforcement Learning for Trajectory Tracking

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arXiv Machine Learning

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Theoretical Foundations and Effective Algorithms for Policy-Aware Simulator Learning

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arXiv Machine Learning

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arXiv Machine Learning

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Solving Markov Decision Processes with Future Information via MPC

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By Shambhuraj Sawant, Akhil S Anand, Dirk Reinhardt, Sebastien Gros

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Wind-Aware Reinforcement Learning Control of a Small Quadrotor Using Learned Onboard Wind Estimation in Simulated Atmospheric Turbulence

Learning from World Feedback: Why Model Uncertainty Fails as a Risk Signal in Model-Based RL

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