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Many control policies used in various applications determine the input or action by solving a convex optimization problem that depends on the current state and some parameters.
Directional stability of automatically steered bodies
N. Minorsky · 1922
Earlier work this paper cites.
Nonlinear programming
H. Kuhn and A. Tucker · 1951
Earlier work this paper cites.
A stochastic approximation method
H. Robbins and S. Monro · 1951
Earlier work this paper cites.
Portfolio selection
H. Markowitz · 1952
Earlier work this paper cites.
Recent advances in finding best operating conditions
R. Anderson · 1953
Earlier work this paper cites.
Dynamic Programming
R. Bellman · 1957
Earlier work this paper cites.
A markovian decision process
R. Bellman · 1957
Earlier work this paper cites.
Contributions to the theory of optimal control
R. Kalman · 1960
Earlier work this paper cites.
On sensitivity analysis in convex quadratic programming problems
J. Boot · 1963
Earlier work this paper cites.
On Bayesian methods for seeking the extremum
J. Močkus · 1975
Earlier work this paper cites.
Minimization by random search techniques
F. Solis and R. Wets · 1981
Earlier work this paper cites.
Reinforcement-Learning Connectionist Systems
R. Williams · 1987
Earlier work this paper cites.
Controller design for uncertain systems via Lyapunov functions
M. Corless and G. Leitmann · 1988
Earlier work this paper cites.
Learning representations by back-propagating errors
D. Rumelhart, G. Hinton, and R. Williams · 1988
Earlier work this paper cites.
Learning to predict by the methods of temporal differences
R. Sutton · 1988
Earlier work this paper cites.
Optimal Control: Linear Quadratic Methods
B. Anderson and J. Moore · 1990
Earlier work this paper cites.
Backpropagation through time: What it does and how to do it
P. Werbos · 1990
Earlier work this paper cites.
Automatic tuning and adaptation for pid controllers-a survey
K. Åström, T. Hägglund, C. Hang, and W. Ho · 1993
Earlier work this paper cites.
Learning long-term dependencies with gradient descent is difficult
Y. Bengio, P. Simard, and P. Frasconi · 1994
Earlier work this paper cites.
Stable function approximation in dynamic programming
G. Gordon · 1995
Earlier work this paper cites.
Neuro-dynamic Programming
D. Bertsekas and J. Tsitsiklis · 1996
Earlier work this paper cites.
Active Portfolio Management: A Quantitative Approach for Producing Superior Returns and Controlling Risk
R. Grinold and R. Kahn · 2000
Earlier work this paper cites.
Completely derandomized self-adaptation in evolution strategies
N. Hansen and A. Ostermeier · 2001
Earlier work this paper cites.
The explicit linear quadratic regulator for constrained systems
A. Bemporad, M. Morari, V. Dua, and E. Pistikopoulos · 2002
Earlier work this paper cites.
The linear programming approach to approximate dynamic programming
D. De Farias and B. Van Roy · 2003
Earlier work this paper cites.
Least squares policy evaluation algorithms with linear function approximation
A. Nedić and D. Bertsekas · 2003
Earlier work this paper cites.
Improved temporal difference methods with linear function approximation
D. Bertsekas, V. Borkar, and A. Nedić · 2004
Earlier work this paper cites.
Convex Optimization
S. Boyd and L. Vandenberghe · 2004
Earlier work this paper cites.
Optimization Methods in Finance
G. Cornuejols and R. Tütüncü · 2006
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Sampling Techniques
W. Cochran · 2007
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Approximate Dynamic Programming: Solving the Curses of Dimensionality
W. Powell · 2007
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A model predictive control framework for industrial turbodiesel engine control
G. Stewart and F. Borrelli · 2008
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Introduction to Derivative-Free Optimization
A. Conn, K. Scheinberg, and L. Vicente · 2009
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Model Predictive Control: Theory and Design
J. Rawlings and D. Mayne · 2009
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Performance bounds for linear stochastic control
Embedded code generation using the OSQP solver
G. Banjac, B. Stellato, N. Moehle, P. Goulart, A. Bemporad, and S. Boyd · 2017
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Dynamic Programming and Optimal Control
D. Bertsekas · 2017
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Predictive Control for Linear and Hybrid Systems
F. Borrelli, A. Bemporad, and M. Morari · 2017
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Multi-period trading via convex optimization
S. Boyd, E. Busseti, S. Diamond, R. Kahn, K. Koh, P. Nystrup, and J. Speth · 2017
Later among the works it cites.
SCS: Splitting conic solver, version 2.1.0
B. O’Donoghue, E. Chu, N. Parikh, and S. Boyd · 2017
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Path integral networks: End-to-end differentiable optimal control
M. Okada, L. Rigazio, and T. Aoshima · 2017
Later among the works it cites.
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Y. Wang and S. Boyd · 2009
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Fast evaluation of quadratic control-Lyapunov policy
Y. Wang and S. Boyd · 2010
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Fast model predictive control using online optimization
Y. Wang and S. Boyd · 2010
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Random search for hyper-parameter optimization
J. Bergstra and Y. Bengio · 2012
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Convex methods for approximate dynamic programming
A. Keshavarz · 2012
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CVXGEN: A code generator for embedded convex optimization
J. Mattingley and S. Boyd · 2012
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Learning model predictive control for iterative tasks: A data-driven control framework
U. Rosolia and F. Borrelli · 2017
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Evolution strategies as a scalable alternative to reinforcement learning
T. Salimans, J. Ho, X. Chen, S. Sidor, and I. Sutskever · 2017
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Proximal policy optimization algorithms
J. Schulman, F. Wolski, P. Dhariwal, A. Radford, and O. Klimov · 2017
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High-speed finite control set model predictive control for power electronics
B. Stellato, T. Geyer, and P. Goulart · 2017
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Learning from the hindsight plan–episodic MPC improvement
A. Tamar, G. Thomas, T. Zhang, S. Levine, and P. Abbeel · 2017
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A rewriting system for convex optimization problems
A. Agrawal, R. Verschueren, S. Diamond, and S. Boyd · 2018
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Differentiable MPC for end-to-end planning and control
B. Amos, I. Jimenez, J. Sacks, B. Boots, and J. Z. Kolter · 2018
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On the differentiability of the solution to convex optimization problems
S. Barratt · 2018
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Stochastic control with affine dynamics and extended quadratic costs
S. Barratt and S. Boyd · 2018
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Optimization methods for large-scale machine learning
L. Bottou, F. Curtis, and J. Nocedal · 2018
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Reinforcement Learning: An Introduction
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Differentiable convex optimization layers
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