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Policy Gradient Methods

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Showing 151–200 of 382 papers

TitleStatusHype
On the Convergence of Discounted Policy Gradient Methods—0
Policy Gradient in Robust MDPs with Global Convergence GuaranteeCode0
An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods—0
Geometry and convergence of natural policy gradient methods—0
Convergence of policy gradient methods for finite-horizon exploratory linear-quadratic control problems—0
Symmetric (Optimistic) Natural Policy Gradient for Multi-agent Learning with Parameter Convergence—0
Policy Gradient Methods for Designing Dynamic Output Feedback Controllers—0
On the convergence of policy gradient methods to Nash equilibria in general stochastic games—0
Linear Convergence of Natural Policy Gradient Methods with Log-Linear Policies—0
SoftTreeMax: Policy Gradient with Tree Search—0
Asynchronous Actor-Critic for Multi-Agent Reinforcement Learning—0
On the Optimization Landscape of Dynamic Output Feedback: A Case Study for Linear Quadratic Regulator—0
The Performance Impact of Combining Agent Factorization with Different Learning Algorithms for Multiagent CoordinationCode0
Natural Policy Gradients In Reinforcement Learning Explained—0
Towards Global Optimality in Cooperative MARL with the Transformation And Distillation Framework—0
Convergence and Price of Anarchy Guarantees of the Softmax Policy Gradient in Markov Potential Games—0
How are policy gradient methods affected by the limits of control?—0
Variance Reduction for Policy-Gradient Methods via Empirical Variance Minimization—0
Learning Dynamics and Generalization in Reinforcement Learning—0
Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Function—0
Momentum-Based Policy Gradient with Second-Order Information—0
Stochastic first-order methods for average-reward Markov decision processes—0
Learning to Constrain Policy Optimization with Virtual Trust Region—0
Independent Natural Policy Gradient Methods for Potential Games: Finite-time Global Convergence with Entropy Regularization—0
Synthesis of Stabilizing Recurrent Equilibrium Network ControllersCode0
Asynchronous, Option-Based Multi-Agent Policy Gradient: A Conditional Reasoning Approach—0
Non-Parametric Stochastic Policy Gradient with Strategic Retreat for Non-Stationary Environment—0
Linear convergence of a policy gradient method for some finite horizon continuous time control problems—0
Policy Learning and Evaluation with Randomized Quasi-Monte Carlo—0
Independent Policy Gradient for Large-Scale Markov Potential Games: Sharper Rates, Function Approximation, and Game-Agnostic Convergence—0
PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method with Probabilistic Gradient Estimation—0
Leveraging class abstraction for commonsense reinforcement learning via residual policy gradient methodsCode0
Homotopic Policy Mirror Descent: Policy Convergence, Implicit Regularization, and Improved Sample Complexity—0
Understanding the Effects of Second-Order Approximations in Natural Policy Gradient Reinforcement LearningCode0
On the Convergence Rates of Policy Gradient Methods—0
Reinforcement Learning based Sequential Batch-sampling for Bayesian Optimal Experimental Design—0
MDPGT: Momentum-based Decentralized Policy Gradient TrackingCode0
Global Convergence Using Policy Gradient Methods for Model-free Markovian Jump Linear Quadratic Control—0
Time Discretization-Invariant Safe Action Repetition for Policy Gradient MethodsCode0
Global Optimality and Finite Sample Analysis of Softmax Off-Policy Actor Critic under State Distribution MismatchCode0
Proximal Policy Optimization with Continuous Bounded Action Space via the Beta Distribution—0
Convergence and Optimality of Policy Gradient Methods in Weakly Smooth Settings—0
Beyond Exact Gradients: Convergence of Stochastic Soft-Max Policy Gradient Methods with Entropy Regularization—0
Local Advantage Actor-Critic for Robust Multi-Agent Deep Reinforcement Learning—0
Stabilizing Dynamical Systems via Policy Gradient Methods—0
Programmatic Reinforcement Learning without Oracles—0
Variance Reduced Domain Randomization for Policy Gradient—0
Efficient Wasserstein and Sinkhorn Policy Optimization—0
Sample-efficient actor-critic algorithms with an etiquette for zero-sum Markov games—0
Actor-Critic Policy Optimization in a Large-Scale Imperfect-Information Game—0
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