Faster Reinforcement Learning by Freezing Slow States
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | Wang, Yijia, Jiang, Daniel R. |
|---|---|
| Format: | Preprint |
| Publié: |
2023
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
Lyapunov Function Consistent Adaptive Network Signal Control with Back Pressure and Reinforcement Learning
par: Ma, Chaolun, et autres
Publié: (2022)
par: Ma, Chaolun, et autres
Publié: (2022)
Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning
par: Mitra, Aritra, et autres
Publié: (2023)
par: Mitra, Aritra, et autres
Publié: (2023)
Action Dependency Graphs for Globally Optimal Coordinated Reinforcement Learning
par: Ding, Jianglin, et autres
Publié: (2025)
par: Ding, Jianglin, et autres
Publié: (2025)
ART for Diffusion Sampling: A Reinforcement Learning Approach to Timestep Schedule
par: Huang, Yilie, et autres
Publié: (2026)
par: Huang, Yilie, et autres
Publié: (2026)
CORL: Reinforcement Learning of MILP Policies Solved via Branch and Bound
par: Anand, Akhil S, et autres
Publié: (2025)
par: Anand, Akhil S, et autres
Publié: (2025)
Sublinear Regret for a Class of Continuous-Time Linear-Quadratic Reinforcement Learning Problems
par: Huang, Yilie, et autres
Publié: (2024)
par: Huang, Yilie, et autres
Publié: (2024)
Infinite-Horizon Reach-Avoid Zero-Sum Games via Deep Reinforcement Learning
par: Li, Jingqi, et autres
Publié: (2022)
par: Li, Jingqi, et autres
Publié: (2022)
Benchmarking Reinforcement Learning via Stochastic Converse Optimality: Generating Systems with Known Optimal Policies
par: Ibrahim, Sinan, et autres
Publié: (2026)
par: Ibrahim, Sinan, et autres
Publié: (2026)
Asynchronous Distributed Reinforcement Learning for LQR Control via Zeroth-Order Block Coordinate Descent
par: Jing, Gangshan, et autres
Publié: (2021)
par: Jing, Gangshan, et autres
Publié: (2021)
Hierarchical Deep Reinforcement Learning Framework for Multi-Year Asset Management Under Budget Constraints
par: Fard, Amir, et autres
Publié: (2025)
par: Fard, Amir, et autres
Publié: (2025)
Data-Driven Exploration for a Class of Continuous-Time Indefinite Linear--Quadratic Reinforcement Learning Problems
par: Huang, Yilie, et autres
Publié: (2025)
par: Huang, Yilie, et autres
Publié: (2025)
Intersection of Reinforcement Learning and Bayesian Optimization for Intelligent Control of Industrial Processes: A Safe MPC-based DPG using Multi-Objective BO
par: Esfahani, Hossein Nejatbakhsh, et autres
Publié: (2025)
par: Esfahani, Hossein Nejatbakhsh, et autres
Publié: (2025)
Bucketized Active Sampling for Learning ACOPF
par: Klamkin, Michael, et autres
Publié: (2022)
par: Klamkin, Michael, et autres
Publié: (2022)
Primitive Agentic First-Order Optimization
par: Sala, R.
Publié: (2024)
par: Sala, R.
Publié: (2024)
PGLearn -- An Open-Source Learning Toolkit for Optimal Power Flow
par: Klamkin, Michael, et autres
Publié: (2025)
par: Klamkin, Michael, et autres
Publié: (2025)
Co-Learning Port-Hamiltonian Systems and Optimal Energy-Shaping Control
par: Kamboj, Ankur, et autres
Publié: (2026)
par: Kamboj, Ankur, et autres
Publié: (2026)
Stabilizing reinforcement learning control: A modular framework for optimizing over all stable behavior
par: Lawrence, Nathan P., et autres
Publié: (2023)
par: Lawrence, Nathan P., et autres
Publié: (2023)
Stochastic Learning of Computational Resource Usage as Graph Structured Multimarginal Schrödinger Bridge
par: Bondar, Georgiy A., et autres
Publié: (2024)
par: Bondar, Georgiy A., et autres
Publié: (2024)
Deep Learning for Sequential Decision Making under Uncertainty: Foundations, Frameworks, and Frontiers
par: Buyuktahtakin, I. Esra
Publié: (2026)
par: Buyuktahtakin, I. Esra
Publié: (2026)
Optimizing Inventory Routing: A Decision-Focused Learning Approach using Neural Networks
par: Islam, MD Shafikul, et autres
Publié: (2023)
par: Islam, MD Shafikul, et autres
Publié: (2023)
Differentiable Optimization for Deep Learning-Enhanced DC Approximation of AC Optimal Power Flow
par: Rosemberg, Andrew, et autres
Publié: (2025)
par: Rosemberg, Andrew, et autres
Publié: (2025)
Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration
par: Ju, Caleb, et autres
Publié: (2024)
par: Ju, Caleb, et autres
Publié: (2024)
Multi-Year Maintenance Planning for Large-Scale Infrastructure Systems: A Novel Network Deep Q-Learning Approach
par: Fard, Amir, et autres
Publié: (2025)
par: Fard, Amir, et autres
Publié: (2025)
Koopman-Assisted Reinforcement Learning
par: Rozwood, Preston, et autres
Publié: (2024)
par: Rozwood, Preston, et autres
Publié: (2024)
Stability of Primal-Dual Gradient Flow Dynamics for Multi-Block Convex Optimization Problems
par: Ozaslan, Ibrahim K., et autres
Publié: (2024)
par: Ozaslan, Ibrahim K., et autres
Publié: (2024)
Convergence and sample complexity of natural policy gradient primal-dual methods for constrained MDPs
par: Ding, Dongsheng, et autres
Publié: (2022)
par: Ding, Dongsheng, et autres
Publié: (2022)
Lyapunov-stable Neural Control for State and Output Feedback: A Novel Formulation
par: Yang, Lujie, et autres
Publié: (2024)
par: Yang, Lujie, et autres
Publié: (2024)
gridfm-datakit-v1: A Python Library for Scalable and Realistic Power Flow and Optimal Power Flow Data Generation
par: Puech, Alban, et autres
Publié: (2025)
par: Puech, Alban, et autres
Publié: (2025)
Multi-Objective Optimization Using Adaptive Distributed Reinforcement Learning
par: Tan, Jing, et autres
Publié: (2024)
par: Tan, Jing, et autres
Publié: (2024)
Active Constraint Learning in High Dimensions from Demonstrations
par: Qiu, Zheng, et autres
Publié: (2025)
par: Qiu, Zheng, et autres
Publié: (2025)
Revisiting LQR Control from the Perspective of Receding-Horizon Policy Gradient
par: Zhang, Xiangyuan, et autres
Publié: (2023)
par: Zhang, Xiangyuan, et autres
Publié: (2023)
On the Convergence of Overparameterized Problems: Inherent Properties of the Compositional Structure of Neural Networks
par: de Oliveira, Arthur Castello Branco, et autres
Publié: (2025)
par: de Oliveira, Arthur Castello Branco, et autres
Publié: (2025)
Achieving Tighter Finite-Time Rates for Heterogeneous Federated Stochastic Approximation under Markovian Sampling
par: Zhu, Feng, et autres
Publié: (2025)
par: Zhu, Feng, et autres
Publié: (2025)
A Riemannian Optimization Perspective of the Gauss-Newton Method for Feedforward Neural Networks
par: Cayci, Semih
Publié: (2024)
par: Cayci, Semih
Publié: (2024)
WARP: A Benchmark for Primal-Dual Warm-Starting of Interior-Point Solvers
par: Suri, Dhruv, et autres
Publié: (2026)
par: Suri, Dhruv, et autres
Publié: (2026)
Nonlinear Non-Gaussian Density Steering with Input and Noise Channel Mismatch: Sinkhorn with Memory for Solving the Control-affine Schrödinger Bridge Problem
par: Bondar, Georgiy A., et autres
Publié: (2026)
par: Bondar, Georgiy A., et autres
Publié: (2026)
Optimal Control Operator Perspective and a Neural Adaptive Spectral Method
par: Feng, Mingquan, et autres
Publié: (2024)
par: Feng, Mingquan, et autres
Publié: (2024)
From Automation to Autonomy in Smart Manufacturing: A Bayesian Optimization Framework for Modeling Multi-Objective Experimentation and Sequential Decision Making
par: Asru, Avijit Saha, et autres
Publié: (2025)
par: Asru, Avijit Saha, et autres
Publié: (2025)
Differentiable Distributionally Robust Optimization Layers
par: Ma, Xutao, et autres
Publié: (2024)
par: Ma, Xutao, et autres
Publié: (2024)
Generative AI and Process Systems Engineering: The Next Frontier
par: Decardi-Nelson, Benjamin, et autres
Publié: (2024)
par: Decardi-Nelson, Benjamin, et autres
Publié: (2024)
Documents similaires
-
Lyapunov Function Consistent Adaptive Network Signal Control with Back Pressure and Reinforcement Learning
par: Ma, Chaolun, et autres
Publié: (2022) -
Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning
par: Mitra, Aritra, et autres
Publié: (2023) -
Action Dependency Graphs for Globally Optimal Coordinated Reinforcement Learning
par: Ding, Jianglin, et autres
Publié: (2025) -
ART for Diffusion Sampling: A Reinforcement Learning Approach to Timestep Schedule
par: Huang, Yilie, et autres
Publié: (2026) -
CORL: Reinforcement Learning of MILP Policies Solved via Branch and Bound
par: Anand, Akhil S, et autres
Publié: (2025)