Towards continual reinforcement learning: A review and perspectives
In this article, we aim to provide a literature review of different formulations and approaches
to continual reinforcement learning (RL), also known as lifelong or non-stationary RL. We …
to continual reinforcement learning (RL), also known as lifelong or non-stationary RL. We …
[HTML][HTML] Review of online learning for control and diagnostics of power converters and drives: Algorithms, implementations and applications
Power converters and motor drives are playing a significant role in the transition towards
sustainable energy systems and transportation electrification. In this context, rich diversity of …
sustainable energy systems and transportation electrification. In this context, rich diversity of …
Adversarially trained actor critic for offline reinforcement learning
CA Cheng, T ** for uncertainty-driven offline reinforcement learning
Offline Reinforcement Learning (RL) aims to learn policies from previously collected
datasets without exploring the environment. Directly applying off-policy algorithms to offline …
datasets without exploring the environment. Directly applying off-policy algorithms to offline …
Settling the sample complexity of model-based offline reinforcement learning
Settling the sample complexity of model-based offline reinforcement learning Page 1 The
Annals of Statistics 2024, Vol. 52, No. 1, 233–260 https://doi.org/10.1214/23-AOS2342 © …
Annals of Statistics 2024, Vol. 52, No. 1, 233–260 https://doi.org/10.1214/23-AOS2342 © …
Hybrid rl: Using both offline and online data can make rl efficient
We consider a hybrid reinforcement learning setting (Hybrid RL), in which an agent has
access to an offline dataset and the ability to collect experience via real-world online …
access to an offline dataset and the ability to collect experience via real-world online …
Efficient reinforcement learning in block mdps: A model-free representation learning approach
We present BRIEE, an algorithm for efficient reinforcement learning in Markov Decision
Processes with block-structured dynamics (ie, Block MDPs), where rich observations are …
Processes with block-structured dynamics (ie, Block MDPs), where rich observations are …