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Model-Agnostic Zeroth-Order Policy Optimization for Meta-Learning of
  Ergodic Linear Quadratic Regulators

Model-Agnostic Zeroth-Order Policy Optimization for Meta-Learning of Ergodic Linear Quadratic Regulators

27 May 2024
Yunian Pan
Quanyan Zhu
ArXivPDFHTML

Papers citing "Model-Agnostic Zeroth-Order Policy Optimization for Meta-Learning of Ergodic Linear Quadratic Regulators"

4 / 4 papers shown
Title
Coreset-Based Task Selection for Sample-Efficient Meta-Reinforcement Learning
Coreset-Based Task Selection for Sample-Efficient Meta-Reinforcement Learning
Donglin Zhan
Leonardo F. Toso
James Anderson
174
3
0
04 Feb 2025
Policy Gradient Methods for the Noisy Linear Quadratic Regulator over a
  Finite Horizon
Policy Gradient Methods for the Noisy Linear Quadratic Regulator over a Finite Horizon
B. Hambly
Renyuan Xu
Huining Yang
56
62
0
20 Nov 2020
Thompson Sampling for Linear-Quadratic Control Problems
Thompson Sampling for Linear-Quadratic Control Problems
Marc Abeille
A. Lazaric
49
55
0
27 Mar 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
823
11,899
0
09 Mar 2017
1