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 1601–1650 of 15113 papers

TitleStatusHype
AnyBipe: An End-to-End Framework for Training and Deploying Bipedal Robots Guided by Large Language ModelsCode1
Optimal Management of Grid-Interactive Efficient Buildings via Safe Reinforcement Learning—0
Digital Twin for Autonomous Guided Vehicles based on Integrated Sensing and Communications—0
Scores as Actions: a framework of fine-tuning diffusion models by continuous-time reinforcement learning—0
Hand-Object Interaction Pretraining from Videos—0
Reinforcement Learning Discovers Efficient Decentralized Graph Path Search StrategiesCode0
The Role of Deep Learning Regularizations on Actors in Offline RLCode0
Learning Efficient Recursive Numeral Systems via Reinforcement Learning—0
Online Decision MetaMorphFormer: A Casual Transformer-Based Reinforcement Learning Framework of Universal Embodied Intelligence—0
Double Successive Over-Relaxation Q-Learning with an Extension to Deep Reinforcement LearningCode0
Automated Data Augmentation for Few-Shot Time Series Forecasting: A Reinforcement Learning Approach Guided by a Model Zoo—0
Superior Computer Chess with Model Predictive Control, Reinforcement Learning, and Rollout—0
BetterBodies: Reinforcement Learning guided Diffusion for Antibody Sequence Design—0
Markov Chain Variance Estimation: A Stochastic Approximation Approach—0
Forward KL Regularized Preference Optimization for Aligning Diffusion Policies—0
BAMDP Shaping: a Unified Theoretical Framework for Intrinsic Motivation and Reward Shaping—0
Semifactual Explanations for Reinforcement LearningCode0
An Introduction to Quantum Reinforcement Learning (QRL)—0
Causality-Driven Reinforcement Learning for Joint Communication and Sensing—0
Reinforcement Learning for Rate Maximization in IRS-aided OWC Networks—0
Reward-Directed Score-Based Diffusion Models via q-Learning—0
Reinforcement Learning-Based Adaptive Load Balancing for Dynamic Cloud Environments—0
Sample and Oracle Efficient Reinforcement Learning for MDPs with Linearly-Realizable Value Functions—0
Reward Guidance for Reinforcement Learning Tasks Based on Large Language Models: The LMGT Framework—0
Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy ChurnCode0
Gaussian-Mixture-Model Q-Functions for Reinforcement Learning by Riemannian Optimization—0
InfraLib: Enabling Reinforcement Learning and Decision-Making for Large-Scale Infrastructure Management—0
Differentiable Discrete Event Simulation for Queuing Network Control—0
CHIRPs: Change-Induced Regret Proxy metrics for Lifelong Reinforcement Learning—0
Robust synchronization and policy adaptation for networked heterogeneous agents—0
Reinforcement Learning Approach to Optimizing Profilometric Sensor Trajectories for Surface Inspection—0
ELO-Rated Sequence Rewards: Advancing Reinforcement Learning ModelsCode0
Enhancing Information Freshness: An AoI Optimized Markov Decision Process Dedicated In the Underwater Task—0
Continual Diffuser (CoD): Mastering Continual Offline Reinforcement Learning with Experience RehearsalCode0
Large Language Models as Efficient Reward Function Searchers for Custom-Environment Multi-Objective Reinforcement Learning—0
Tractable Offline Learning of Regular Decision Processes—0
State and Action Factorization in Power Grids—0
Reinforcement Learning-enabled Satellite Constellation Reconfiguration and Retasking for Mission-Critical Applications—0
Grounding Language Models in Autonomous Loco-manipulation Tasks—0
MOOSS: Mask-Enhanced Temporal Contrastive Learning for Smooth State Evolution in Visual Reinforcement LearningCode0
Enhancing Sample Efficiency and Exploration in Reinforcement Learning through the Integration of Diffusion Models and Proximal Policy OptimizationCode2
Diffusion Policy Policy OptimizationCode4
AgGym: An agricultural biotic stress simulation environment for ultra-precision management planningCode0
Foundations of Multivariate Distributional Reinforcement Learning—0
Robust off-policy Reinforcement Learning via Soft Constrained Adversary—0
Traffic expertise meets residual RL: Knowledge-informed model-based residual reinforcement learning for CAV trajectory controlCode1
Discovery of False Data Injection Schemes on Frequency Controllers with Reinforcement Learning—0
AdapShare: An RL-Based Dynamic Spectrum Sharing Solution for O-RAN—0
On Convergence of Average-Reward Q-Learning in Weakly Communicating Markov Decision Processes—0
RAIN: Reinforcement Algorithms for Improving Numerical Weather and Climate ModelsCode0
Show:102550
← PrevPage 33 of 303Next →

Benchmark Results

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