SOTAVerified

Reinforcement Learning (RL)

Reinforcement Learning (RL) involves training an agent to take actions in an environment to maximize a cumulative reward signal. The agent interacts with the environment and learns by receiving feedback in the form of rewards or punishments for its actions. The goal of reinforcement learning is to find the optimal policy or decision-making strategy that maximizes the long-term reward.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3101–3150 of 15113 papers

TitleStatusHype
Enhancing Online Reinforcement Learning with Meta-Learned Objective from Offline DataCode0
RbRL2.0: Integrated Reward and Policy Learning for Rating-based Reinforcement Learning—0
Average Reward Reinforcement Learning for Wireless Radio Resource Management—0
DRDT3: Diffusion-Refined Decision Test-Time Training Model—0
Pareto Set Learning for Multi-Objective Reinforcement Learning—0
An Empirical Study of Deep Reinforcement Learning in Continuing TasksCode0
AlgoPilot: Fully Autonomous Program Synthesis Without Human-Written Programs—0
A Hybrid Framework for Reinsurance Optimization: Integrating Generative Models and Reinforcement LearningCode0
Hierarchical Reinforcement Learning for Optimal Agent Grouping in Cooperative Systems—0
Real-Time Integrated Dispatching and Idle Fleet Steering with Deep Reinforcement Learning for A Meal Delivery Platform—0
Diffusion Models for Smarter UAVs: Decision-Making and Modeling—0
Investigating the Impact of Observation Space Design Choices On Training Reinforcement Learning Solutions for Spacecraft Problems—0
Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing—0
Smart Imitator: Learning from Imperfect Clinical DecisionsCode0
LearningFlow: Automated Policy Learning Workflow for Urban Driving with Large Language Models—0
Risk-averse policies for natural gas futures trading using distributional reinforcement learning—0
Deep Transfer Q-Learning for Offline Non-Stationary Reinforcement Learning—0
Safe Reinforcement Learning with Minimal Supervision—0
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement LearningCode0
Explainable Reinforcement Learning via Temporal Policy Decomposition—0
Run-and-tumble chemotaxis using reinforcement learning—0
Interpretable Recognition of Fused Magnesium Furnace Working Conditions with Deep Convolutional Stochastic Configuration Networks—0
Digital Twin Aided Channel Estimation: Zone-Specific Subspace Prediction and CalibrationCode0
Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes—0
AMM: Adaptive Modularized Reinforcement Model for Multi-city Traffic Signal Control—0
A New Interpretation of the Certainty-Equivalence Approach for PAC Reinforcement Learning with a Generative Model—0
Representation Convergence: Mutual Distillation is Secretly a Form of RegularizationCode0
SR-Reward: Taking The Path More Traveled—0
Proposing Hierarchical Goal-Conditioned Policy Planning in Multi-Goal Reinforcement Learning—0
On the Statistical Complexity for Offline and Low-Adaptive Reinforcement Learning with Structures—0
Noise-Resilient Symbolic Regression with Dynamic Gating Reinforcement LearningCode0
A Graphical Approach to State Variable Selection in Off-policy Learning—0
RaSS: Improving Denoising Diffusion Samplers with Reinforced Active Sampling Scheduler—0
Hybridising Reinforcement Learning and Heuristics for Hierarchical Directed Arc Routing ProblemsCode0
Neural Motion Simulator Pushing the Limit of World Models in Reinforcement Learning—0
Towards Unraveling and Improving Generalization in World Models—0
FORM: Learning Expressive and Transferable First-Order Logic Reward Machines—0
Weber-Fechner Law in Temporal Difference learning derived from Control as Inference—0
UnrealZoo: Enriching Photo-realistic Virtual Worlds for Embodied AI—0
An Unsupervised Anomaly Detection in Electricity Consumption Using Reinforcement Learning and Time Series Forest Based Framework—0
Isoperimetry is All We Need: Langevin Posterior Sampling for RL with Sublinear Regret—0
Enhancing Code LLMs with Reinforcement Learning in Code Generation: A Survey—0
Dynamic Optimization of Storage Systems Using Reinforcement Learning Techniques—0
Goal-Conditioned Data Augmentation for Offline Reinforcement Learning—0
Efficient and Scalable Deep Reinforcement Learning for Mean Field Control GamesCode0
Election of Collaborators via Reinforcement Learning for Federated Brain Tumor Segmentation—0
Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization—0
xSRL: Safety-Aware Explainable Reinforcement Learning -- Safety as a Product of ExplainabilityCode0
Provably Efficient Exploration in Reward Machines with Low Regret—0
A Reinforcement Learning-Based Task Mapping Method to Improve the Reliability of Clustered Manycores—0
Show:102550
← PrevPage 63 of 303Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PPGMean Normalized Performance0.76—Unverified
2PPOMean Normalized Performance0.58—Unverified