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Advanced Building Control via Deep Reinforcement Learning
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/bf00992696openalex-snapshot
Simple statistical gradient-following algorithms for connectionist reinforcement learning
inferredcites →https://doi.org/10.1016/j.egypro.2019.01.494openalex-snapshot
Advanced Building Control via Deep Reinforcement Learning
inferredcites →https://doi.org/10.1016/j.enbuild.2017.10.017openalex-snapshot
Evaluation of a cost-responsive supply air temperature reset strategy in an office building
inferredcites →https://doi.org/10.1016/s1364-6613(99)01327-3openalex-snapshot
Is imitation learning the route to humanoid robots?
inferredcites →https://doi.org/10.1038/nature14236openalex-snapshot
Human-level control through deep reinforcement learning
inferredcites →https://doi.org/10.1038/nature16961openalex-snapshot
Mastering the game of Go with deep neural networks and tree search
inferredcites →https://doi.org/10.1038/sj.jea.7500165openalex-snapshot
The National Human Activity Pattern Survey (NHAPS): a resource for assessing exposure to environmental pollutants
inferredcites →https://doi.org/10.1109/cdc.2018.8618996openalex-snapshot
Control-Theoretic Analysis of Smoothness for Stability-Certified Reinforcement Learning
inferredcites →https://doi.org/10.1109/cvpr.2009.5206848openalex-snapshot
ImageNet: A large-scale hierarchical image database
inferredcites →https://doi.org/10.1214/aos/1176343541openalex-snapshot
Importance Sampling in the Monte Carlo Study of Sequential Tests
inferredcites →https://doi.org/10.21437/icslp.2000-743openalex-snapshot
The aurora experimental framework for the performance evaluation of speech recognition systems under noisy conditions
inferredcites →https://doi.org/10.26868/30680611.2012.09a_2_kimopenalex-snapshot
Reduced-Order Building Modeling for Application to Model-Based Predictive Control
inferredcites →https://doi.org/10.48550/arxiv.1509.02971openalex-snapshot
Continuous control with deep reinforcement learning
inferredcites →https://doi.org/10.48550/arxiv.1604.06778openalex-snapshot
Benchmarking Deep Reinforcement Learning for Continuous Control
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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ОБУЧЕНИЕ С ПОДКРЕПЛЕНИЕМ С ВНЕШНИМ УЧИТЕЛЕМ ДЛЯ УПРАВЛЕНИЯ ЭНЕРГООБЪЕКТАМИ
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