OFFER: Off-environment reinforcement learning
Policy gradient methods have been widely applied in reinforcement learning. For reasons of safety and cost, learning is often conducted using a simulator. However, learning in simulation does not traditionally utilise the opportunity to improve learning by adjusting certain environment variables - s...
Автори: | Ciosek, K, Whiteson, S |
---|---|
Формат: | Conference item |
Мова: | English |
Опубліковано: |
AAAI Press
2017
|
Схожі ресурси
-
Expected policy gradients for reinforcement learning
за авторством: Ciosek, K, та інші
Опубліковано: (2020) -
Robust reinforcement learning with Bayesian optimisation and quadrature
за авторством: Paul, S, та інші
Опубліковано: (2020) -
Expected policy gradients
за авторством: Ciosek, K, та інші
Опубліковано: (2018) -
Loaded DiCE: Trading off bias and variance in any-order score function gradient estimators for reinforcement learning
за авторством: Farquhar, G, та інші
Опубліковано: (2019) -
Fourier policy gradients
за авторством: Fellows, M, та інші
Опубліковано: (2018)