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Global Convergence of Policy Gradient Primal-Dual Methods for Risk-Constrained LQRs
Feiran Zhao, Keyou You,
Tamer Basar
Electrical and Computer Engineering
Coordinated Science Lab
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Dive into the research topics of 'Global Convergence of Policy Gradient Primal-Dual Methods for Risk-Constrained LQRs'. Together they form a unique fingerprint.
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Keyphrases
Optimization Approach
100%
Primal-dual Algorithm
100%
Policy Optimization
100%
Global Convergence
100%
Policy Gradient
100%
Risk-constrained
100%
Constrained LQR
100%
Sampling Methods
50%
Convergence Guarantee
50%
Performance Metrics
50%
Constrained Optimization Problem
50%
Theoretical Understanding
50%
Time-invariant
50%
Gradient-based
50%
System Trajectory
50%
Optimal Policy
50%
Optimal Control Theory
50%
Linear Quadratic Regulator
50%
Strong Duality
50%
Nonconvex Optimization
50%
Lagrangian Function
50%
Affine Structure
50%
Lipschitz Continuous Gradient
50%
Design Policy
50%
Reinforcement Learning Problems
50%
Local Lipschitz Continuous
50%
Mathematics
Optimal Control Theory
100%
Constrained Optimization Problem
100%
Optimal Policy
100%
Strong Duality
100%
Lagrangian Function
100%
Computer Science
Lagrangian Function
50%