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 2901–2950 of 15113 papers

TitleStatusHype
DreamerV3 for Traffic Signal Control: Hyperparameter Tuning and Performance—0
All Roads Lead to Likelihood: The Value of Reinforcement Learning in Fine-Tuning—0
Accelerating Multi-Task Temporal Difference Learning under Low-Rank Representation—0
What's Behind PPO's Collapse in Long-CoT? Value Optimization Holds the Secret—0
Active Alignments of Lens Systems with Reinforcement Learning—0
Adversarial Agents: Black-Box Evasion Attacks with Reinforcement Learning—0
Quality-Driven Curation of Remote Sensing Vision-Language Data via Learned Scoring Models—0
Minimax Optimal Reinforcement Learning with Quasi-Optimism—0
Scalable Reinforcement Learning for Virtual Machine Scheduling—0
Towards Understanding the Benefit of Multitask Representation Learning in Decision Process—0
Never too Prim to Swim: An LLM-Enhanced RL-based Adaptive S-Surface Controller for AUVs under Extreme Sea Conditions—0
Adaptive Reinforcement Learning for State Avoidance in Discrete Event Systems—0
Multimodal Dreaming: A Global Workspace Approach to World Model-Based Reinforcement Learning—0
Subtask-Aware Visual Reward Learning from Segmented Demonstrations—0
Hierarchical and Modular Network on Non-prehensile Manipulation in General Environments—0
Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learning—0
Improving the Efficiency of a Deep Reinforcement Learning-Based Power Management System for HPC Clusters Using Curriculum Learning—0
AutoBS: Autonomous Base Station Deployment with Reinforcement Learning and Digital Network TwinsCode0
Accelerating Model-Based Reinforcement Learning with State-Space World Models—0
On the Importance of Reward Design in Reinforcement Learning-based Dynamic Algorithm Configuration: A Case Study on OneMax with (1+(λ,λ))-GACode0
R1-T1: Fully Incentivizing Translation Capability in LLMs via Reasoning Learning—0
CarPlanner: Consistent Auto-regressive Trajectory Planning for Large-scale Reinforcement Learning in Autonomous Driving—0
Efficient Reinforcement Learning by Guiding Generalist World Models with Non-Curated Data—0
WOFOSTGym: A Crop Simulator for Learning Annual and Perennial Crop Management StrategiesCode0
Distill Not Only Data but Also Rewards: Can Smaller Language Models Surpass Larger Ones?—0
Error-related Potential driven Reinforcement Learning for adaptive Brain-Computer Interfaces—0
FetchBot: Object Fetching in Cluttered Shelves via Zero-Shot Sim2Real—0
SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution—0
Safe Multi-Agent Navigation guided by Goal-Conditioned Safe Reinforcement LearningCode0
From Perceptions to Decisions: Wildfire Evacuation Decision Prediction with Behavioral Theory-informed LLMsCode0
Predicting Liquidity-Aware Bond Yields using Causal GANs and Deep Reinforcement Learning with LLM Evaluation—0
Humanoid Whole-Body Locomotion on Narrow Terrain via Dynamic Balance and Reinforcement Learning—0
Survey on Strategic Mining in Blockchain: A Reinforcement Learning Approach—0
Yes, Q-learning Helps Offline In-Context RL—0
Ensemble RL through Classifier Models: Enhancing Risk-Return Trade-offs in Trading Strategies—0
Toward Dependency Dynamics in Multi-Agent Reinforcement Learning for Traffic Signal Control—0
Together We Rise: Optimizing Real-Time Multi-Robot Task Allocation using Coordinated Heterogeneous Plays—0
Statistical Inference in Reinforcement Learning: A Selective SurveyCode0
An Autonomous Network Orchestration Framework Integrating Large Language Models with Continual Reinforcement Learning—0
The Evolving Landscape of LLM- and VLM-Integrated Reinforcement Learning—0
On the Design of Safe Continual RL Methods for Control of Nonlinear SystemsCode0
Hyperspherical Normalization for Scalable Deep Reinforcement Learning—0
Reinforcement Learning with Graph Attention for Routing and Wavelength Assignment with Lightpath Reuse—0
MLGym: A New Framework and Benchmark for Advancing AI Research Agents—0
Learning from Reward-Free Offline Data: A Case for Planning with Latent Dynamics Models—0
Discovering highly efficient low-weight quantum error-correcting codes with reinforcement learning—0
Reinforcement Learning for Ultrasound Image Analysis A Comprehensive Review of Advances and Applications—0
Comprehensive Review on the Control of Heat Pumps for Energy Flexibility in Distribution Networks—0
Optimizing Gene-Based Testing for Antibiotic Resistance Prediction—0
Uncertainty quantification for Markov chains with application to temporal difference learning—0
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Benchmark Results

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