Reinforcement learning for selective key applications in power systems: Recent advances and future challenges
With large-scale integration of renewable generation and distributed energy resources,
modern power systems are confronted with new operational challenges, such as growing …
modern power systems are confronted with new operational challenges, such as growing …
Exploiting linear models for model-free nonlinear control: A provably convergent policy gradient approach
Model-free learning-based control methods have seen great success recently. However,
such methods typically suffer from poor sample complexity and limited convergence …
such methods typically suffer from poor sample complexity and limited convergence …
Model-based reinforcement learning with multi-step plan value estimation
A promising way to improve the sample efficiency of reinforcement learning is model-based
methods, in which many explorations and evaluations can happen in the learned models to …
methods, in which many explorations and evaluations can happen in the learned models to …
Applications of the free energy principle to machine learning and neuroscience
B Millidge - arxiv preprint arxiv:2107.00140, 2021 - arxiv.org
In this PhD thesis, we explore and apply methods inspired by the free energy principle to two
important areas in machine learning and neuroscience. The free energy principle is a …
important areas in machine learning and neuroscience. The free energy principle is a …
Any-step Dynamics Model Improves Future Predictions for Online and Offline Reinforcement Learning
Model-based methods in reinforcement learning offer a promising approach to enhance
data efficiency by facilitating policy exploration within a dynamics model. However …
data efficiency by facilitating policy exploration within a dynamics model. However …
Role of reinforcement learning for risk‐based robust control of cyber‐physical energy systems
Critical infrastructures such as cyber‐physical energy systems (CPS‐E) integrate information
flow and physical operations that are vulnerable to natural and targeted failures. Safe …
flow and physical operations that are vulnerable to natural and targeted failures. Safe …