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Imitative Learning for Online Planning in Microgrids.

, , , , and . DARE, volume 9518 of Lecture Notes in Computer Science, page 1-15. Springer, (2015)

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On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability (Extended Abstract)., , , , and . IJCAI, page 5055-5059. ijcai.org, (2020)Journal track.Fuzzy Approximation for Convergent Model-Based Reinforcement Learning., , , and . FUZZ-IEEE, page 1-6. IEEE, (2007)Comprehensive Review on Static and Dynamic Distribution Network Reconfiguration Methodologies., , , and . IEEE Access, (2024)Imitative Learning for Online Planning in Microgrids., , , , and . DARE, volume 9518 of Lecture Notes in Computer Science, page 1-15. Springer, (2015)Warming-up recurrent neural networks to maximize reachable multi-stability greatly improves learning., , and . CoRR, (2021)Recurrent networks, hidden states and beliefs in partially observable environments., , and . CoRR, (2022)Near Optimal Closed-Loop Control. Application to Electric Power Systems.. University of Liège, Belgium, (2003)Assessing the Economic Value of Renewable Resource Complementarity for Power Systems: an ENTSO-E Study., , , , , , , and . CoRR, (2020)Optimal discovery with probabilistic expert advice., , and . CDC, page 6808-6812. IEEE, (2012)Impacts of spatial and temporal resolutions on the near-optimal spaces of energy system optimisation models., and . ISGT EUROPE, page 1-5. IEEE, (2023)