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 3826–3850 of 15113 papers

TitleStatusHype
CIMRL: Combining IMitation and Reinforcement Learning for Safe Autonomous Driving—0
Residual Learning and Context Encoding for Adaptive Offline-to-Online Reinforcement LearningCode0
Scaling Value Iteration Networks to 5000 Layers for Extreme Long-Term Planning—0
When Do Skills Help Reinforcement Learning? A Theoretical Analysis of Temporal AbstractionsCode0
Reinforcement Learning to Disentangle Multiqubit Quantum States from Partial ObservationsCode0
RILe: Reinforced Imitation Learning—0
Toward Enhanced Reinforcement Learning-Based Resource Management via Digital Twin: Opportunities, Applications, and Challenges—0
Hybrid Reinforcement Learning from Offline Observation Alone—0
Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning—0
Unifying Interpretability and Explainability for Alzheimer's Disease Progression PredictionCode0
Enhanced Gene Selection in Single-Cell Genomics: Pre-Filtering Synergy and Reinforced Optimization—0
Learning Reward and Policy Jointly from Demonstration and Preference Improves Alignment—0
Integrating Domain Knowledge for handling Limited Data in Offline RL—0
CHARME: A chain-based reinforcement learning approach for the minor embedding problem—0
EXPIL: Explanatory Predicate Invention for Learning in GamesCode0
Discovering Multiple Solutions from a Single Task in Offline Reinforcement Learning—0
Deep Multi-Objective Reinforcement Learning for Utility-Based Infrastructural Maintenance OptimizationCode0
Decoupling regularization from the action spaceCode0
Is Value Functions Estimation with Classification Plug-and-play for Offline Reinforcement Learning?Code0
STARLING: Self-supervised Training of Text-based Reinforcement Learning Agent with Large Language ModelsCode0
Decision Mamba: A Multi-Grained State Space Model with Self-Evolution Regularization for Offline RLCode0
Enhanced Flight Envelope Protection: A Novel Reinforcement Learning Approach—0
Diffusion-based Reinforcement Learning for Dynamic UAV-assisted Vehicle Twins Migration in Vehicular Metaverses—0
Optimizing Automatic Differentiation with Deep Reinforcement Learning—0
Sim-to-Real Transfer of Deep Reinforcement Learning Agents for Online Coverage Path Planning—0
Show:102550
← PrevPage 154 of 605Next →

Benchmark Results

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