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pro vyhledávání: '"Cater, Evan"'
Autor:
Santhumayor, Brandon A., Chen, Adrian, Pelcher, Isabelle, Cater, Evan, Mishra, Akash, Ward, Max, White, Timothy G., Schulder, Michael, Sciubba, Daniel M., Tracey, Kevin J., Baum, Griffin R.
Publikováno v:
In World Neurosurgery September 2024 189:249-255
When environmental interaction is expensive, model-based reinforcement learning offers a solution by planning ahead and avoiding costly mistakes. Model-based agents typically learn a single-step transition model. In this paper, we propose a multi-ste
Externí odkaz:
http://arxiv.org/abs/1811.00128
Tailoring the presentation of information to the needs of individual students leads to massive gains in student outcomes~\cite{bloom19842}. This finding is likely due to the fact that different students learn differently, perhaps as a result of varia
Externí odkaz:
http://arxiv.org/abs/1809.10025
Learning a generative model is a key component of model-based reinforcement learning. Though learning a good model in the tabular setting is a simple task, learning a useful model in the approximate setting is challenging. In this context, an importa
Externí odkaz:
http://arxiv.org/abs/1806.01265
Publikováno v:
ACM International Conference Proceeding Series; 3/23/2020, p422-427, 6p