- Home
- Publications
- Publication Search
- Publication Details
Title
Control of chaotic systems by deep reinforcement learning
Authors
Keywords
-
Journal
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
Volume 475, Issue 2231, Pages 20190351
Publisher
The Royal Society
Online
2019-11-06
DOI
10.1098/rspa.2019.0351
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Artificial neural networks trained through deep reinforcement learning discover control strategies for active flow control
- (2019) Jean Rabault et al. JOURNAL OF FLUID MECHANICS
- A bounded actor–critic reinforcement learning algorithm applied to airline revenue management
- (2019) Ryan J. Lawhead et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- High-dimensional stochastic optimal control using continuous tensor decompositions
- (2018) Alex Gorodetsky et al. INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
- Efficient collective swimming by harnessing vortices through deep reinforcement learning
- (2018) Siddhartha Verma et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Mastering the game of Go without human knowledge
- (2017) David Silver et al. NATURE
- Nonlinear optimal control of bypass transition in a boundary layer flow
- (2017) Dandan Xiao et al. PHYSICS OF FLUIDS
- Linear Closed-Loop Control of Fluid Instabilities and Noise-Induced Perturbations: A Review of Approaches and Tools1
- (2016) Denis Sipp et al. Applied Mechanics Reviews
- Edge states as mediators of bypass transition in boundary-layer flows
- (2016) T. Khapko et al. JOURNAL OF FLUID MECHANICS
- Methods for solution of large optimal control problems that bypass open-loop model reduction
- (2016) Thomas Bewley et al. MECCANICA
- A statistical learning strategy for closed-loop control of fluid flows
- (2016) Florimond Guéniat et al. THEORETICAL AND COMPUTATIONAL FLUID DYNAMICS
- Closed-Loop Turbulence Control: Progress and Challenges
- (2015) Steven L. Brunton et al. Applied Mechanics Reviews
- Closed-loop separation control using machine learning
- (2015) N. Gautier et al. JOURNAL OF FLUID MECHANICS
- Human-level control through deep reinforcement learning
- (2015) Volodymyr Mnih et al. NATURE
- Adaptive and model-based control theory applied to convectively unstable flows
- (2014) Nicolo Fabbiane et al. Applied Mechanics Reviews
- Adjoint Equations in Stability Analysis
- (2013) Paolo Luchini et al. Annual Review of Fluid Mechanics
- Nonlinear control of unsteady finite-amplitude perturbations in the Blasius boundary-layer flow
- (2013) S. Cherubini et al. JOURNAL OF FLUID MECHANICS
- On the State Space Geometry of the Kuramoto–Sivashinsky Flow in a Periodic Domain
- (2010) Predrag Cvitanović et al. SIAM JOURNAL ON APPLIED DYNAMICAL SYSTEMS
- Reduced-order models for control of fluids using the eigensystem realization algorithm
- (2010) Zhanhua Ma et al. THEORETICAL AND COMPUTATIONAL FLUID DYNAMICS
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExplorePublish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn More