Image de couverture de livre

Beacon, a lightweight deep reinforcement learning benchmark library for flow control

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Viquerat, Jonathan, Meliga, Philippe, Jeken, Pablo, Hachem, Elie
Format:	Preprint
Publié:	2024
Sujets:	Computational Physics Machine Learning Systems and Control
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Dragonfly: a modular deep reinforcement learning library
par: Viquerat, Jonathan, et autres
Publié: (2025)

Automated discovery of finite volume schemes using Graph Neural Networks
par: Garnier, Paul, et autres
Publié: (2025)

Multi-Grid Graph Neural Networks with Self-Attention for Computational Mechanics
par: Garnier, Paul, et autres
Publié: (2024)

A modular framework for stabilizing deep reinforcement learning control
par: Lawrence, Nathan P., et autres
Publié: (2023)

TRELLIS-Enhanced Surface Features for Comprehensive Intracranial Aneurysm Analysis
par: Hervé, Clément, et autres
Publié: (2025)

A review on Deep Reinforcement Learning for Fluid Mechanics
par: Garnier, Paul, et autres
Publié: (2019)

Autonomous vehicle decision and control through reinforcement learning with traffic flow randomization
par: Lin, Yuan, et autres
Publié: (2024)

Load constrained wind farm flow control through multi-objective multi-agent reinforcement learning
par: Åstrand, Teodor, et autres
Publié: (2026)

GreenLight-Gym: Reinforcement learning benchmark environment for control of greenhouse production systems
par: van Laatum, Bart, et autres
Publié: (2024)

Graph Deep Learning for Intracranial Aneurysm Blood Flow Simulation and Risk Assessment
par: Garnier, Paul, et autres
Publié: (2025)

Computationally efficient Gauss-Newton reinforcement learning for model predictive control
par: Brandner, Dean, et autres
Publié: (2025)

Training Transformers for Mesh-Based Simulations
par: Garnier, Paul, et autres
Publié: (2025)

Interpretable reinforcement learning for heat pump control through asymmetric differentiable decision trees
par: Van Puyvelde, Toon, 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)

Distill2Explain: Differentiable decision trees for explainable reinforcement learning in energy application controllers
par: Gokhale, Gargya, et autres
Publié: (2024)

MeshMask: Physics-Based Simulations with Masked Graph Neural Networks
par: Garnier, Paul, et autres
Publié: (2025)

Data-assimilated model-informed reinforcement learning
par: Ozan, Defne E., et autres
Publié: (2025)

Natural-gas storage modelling by deep reinforcement learning
par: Balaconi, Tiziano, et autres
Publié: (2025)

Multi-agent deep reinforcement learning with centralized training and decentralized execution for transportation infrastructure management
par: Saifullah, M., et autres
Publié: (2024)

How to craft a deep reinforcement learning policy for wind farm flow control
par: Kadoche, Elie, et autres
Publié: (2025)

Falsification-driven reinforcement learning for maritime motion planning
par: Müller, Marlon, et autres
Publié: (2025)

Scalable spectral representations for multi-agent reinforcement learning in network MDPs
par: Ren, Zhaolin, et autres
Publié: (2024)

MPCritic: A plug-and-play MPC architecture for reinforcement learning
par: Lawrence, Nathan P., et autres
Publié: (2025)

Aerobatic maneuvers in insect-scale flapping-wing aerial robots via deep-learned robust tube model predictive control
par: Hsiao, Yi-Hsuan, et autres
Publié: (2025)

Exploiting inter-agent coupling information for efficient reinforcement learning of cooperative LQR
par: Syed, Shahbaz P Qadri, et autres
Publié: (2025)

Stabilizing reinforcement learning control: A modular framework for optimizing over all stable behavior
par: Lawrence, Nathan P., et autres
Publié: (2023)

Deep reinforcement learning-based spacecraft attitude control with pointing keep-out constraint
par: Yang, Juntang, et autres
Publié: (2025)

A dual mode adaptive basal-bolus advisor based on reinforcement learning
par: Sun, Qingnan, et autres
Publié: (2019)

Real-world validation of safe reinforcement learning, model predictive control and decision tree-based home energy management systems
par: Ruddick, Julian, et autres
Publié: (2024)

Beyond expected value: geometric mean optimization for long-term policy performance in reinforcement learning
par: Sheng, Xinyi, et autres
Publié: (2025)

Independent policy gradient-based reinforcement learning for economic and reliable energy management of multi-microgrid systems
par: Hu, Junkai, et autres
Publié: (2025)

Curriculum Learning for Mesh-based simulations
par: Garnier, Paul, et autres
Publié: (2025)

Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control
par: Zhong, Yaofeng Desmond, et autres
Publié: (2019)

Friction on Demand: A Generative Framework for the Inverse Design of Metainterfaces
par: Mouton, Valentin, et autres
Publié: (2025)

Learning Enhanced Ensemble Filters
par: Bach, Eviatar, et autres
Publié: (2025)

Inverse Modeling of Dielectric Response in Time Domain using Physics-Informed Neural Networks
par: Esenov, Emir, et autres
Publié: (2025)

Fast Bayesian equipment condition monitoring via simulation based inference: applications to heat exchanger health
par: Collett, Peter, et autres
Publié: (2026)

Contingency-constrained economic dispatch with safe reinforcement learning
par: Eichelbeck, Michael, et autres
Publié: (2022)

Efficient model predictive control for nonlinear systems modelled by deep neural networks
par: Lan, Jianglin
Publié: (2024)

Error estimation for physics-informed neural networks with implicit Runge-Kutta methods
par: Stiasny, Jochen, et autres
Publié: (2024)