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Policy Gradient Methods

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Showing 51–100 of 382 papers

TitleStatusHype
Entropy annealing for policy mirror descent in continuous time and space—0
Mollification Effects of Policy Gradient Methods—0
Linear Function Approximation as a Computationally Efficient Method to Solve Classical Reinforcement Learning Challenges—0
Matrix Low-Rank Approximation For Policy Gradient MethodsCode0
Policy Gradient Methods for Risk-Sensitive Distributional Reinforcement Learning with Provable Convergence—0
Almost sure convergence rates of stochastic gradient methods under gradient domination—0
An Initial Introduction to Cooperative Multi-Agent Reinforcement Learning—0
Federated Reinforcement Learning with Constraint Heterogeneity—0
Off-OAB: Off-Policy Policy Gradient Method with Optimal Action-Dependent Baseline—0
Information-Theoretic Opacity-Enforcement in Markov Decision Processes—0
Control randomisation approach for policy gradient and application to reinforcement learning in optimal switching—0
Actor-Critic Reinforcement Learning with Phased Actor—0
Intervention-Assisted Policy Gradient Methods for Online Stochastic Queuing Network Optimization: Technical Report—0
Elementary Analysis of Policy Gradient Methods—0
Self-Improvement for Neural Combinatorial Optimization: Sample without Replacement, but ImprovementCode1
ReAct Meets ActRe: When Language Agents Enjoy Training Data Autonomy—0
Towards Global Optimality for Practical Average Reward Reinforcement Learning without Mixing Time Oracles—0
Global Convergence Guarantees for Federated Policy Gradient Methods with Adversaries—0
Towards Efficient Risk-Sensitive Policy Gradient: An Iteration Complexity Analysis—0
Provable Policy Gradient Methods for Average-Reward Markov Potential Games—0
Fill-and-Spill: Deep Reinforcement Learning Policy Gradient Methods for Reservoir Operation Decision and Control—0
Stabilizing Policy Gradients for Stochastic Differential Equations via Consistency with Perturbation Process—0
Towards Provable Log Density Policy Gradient—0
Reusing Historical Trajectories in Natural Policy Gradient via Importance Sampling: Convergence and Convergence Rate—0
When Do Off-Policy and On-Policy Policy Gradient Methods Align?—0
Identifying Policy Gradient Subspaces—0
Global Convergence of Natural Policy Gradient with Hessian-aided Momentum Variance Reduction—0
Training Diffusion Models Towards Diverse Image Generation with Reinforcement Learning—0
Optimistic Policy Gradient in Multi-Player Markov Games with a Single Controller: Convergence Beyond the Minty Property—0
Privacy Preserving Multi-Agent Reinforcement Learning in Supply Chains—0
RL Dreams: Policy Gradient Optimization for Score Distillation based 3D Generation—0
Score-Aware Policy-Gradient Methods and Performance Guarantees using Local Lyapunov Conditions: Applications to Product-Form Stochastic Networks and Queueing Systems—0
Predictable Reinforcement Learning Dynamics through Entropy Rate MinimizationCode0
A Large Deviations Perspective on Policy Gradient Algorithms—0
Clipped-Objective Policy Gradients for Pessimistic Policy OptimizationCode0
On the Second-Order Convergence of Biased Policy Gradient Algorithms—0
Riemannian stochastic optimization methods avoid strict saddle points—0
Federated Natural Policy Gradient and Actor Critic Methods for Multi-task Reinforcement Learning—0
Optimization Landscape of Policy Gradient Methods for Discrete-time Static Output Feedback—0
Accelerated Policy Gradient: On the Convergence Rates of the Nesterov Momentum for Reinforcement LearningCode0
f-Policy Gradients: A General Framework for Goal Conditioned RL using f-Divergences—0
Global Convergence of Policy Gradient Methods in Reinforcement Learning, Games and Control—0
Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Methods—0
Beyond Stationarity: Convergence Analysis of Stochastic Softmax Policy Gradient Methods—0
Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds—0
Oracle Complexity Reduction for Model-free LQR: A Stochastic Variance-Reduced Policy Gradient ApproachCode0
Learning Zero-Sum Linear Quadratic Games with Improved Sample Complexity and Last-Iterate ConvergenceCode0
Commodities Trading through Deep Policy Gradient Methods—0
Hindsight-DICE: Stable Credit Assignment for Deep Reinforcement LearningCode0
Enabling Efficient, Reliable Real-World Reinforcement Learning with Approximate Physics-Based ModelsCode0
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