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 1101–1125 of 15113 papers

TitleStatusHype
Proposing Hierarchical Goal-Conditioned Policy Planning in Multi-Goal Reinforcement Learning—0
Noise-Resilient Symbolic Regression with Dynamic Gating Reinforcement LearningCode0
RaSS: Improving Denoising Diffusion Samplers with Reinforced Active Sampling Scheduler—0
Neural Motion Simulator Pushing the Limit of World Models in Reinforcement Learning—0
A Graphical Approach to State Variable Selection in Off-policy Learning—0
Hybridising Reinforcement Learning and Heuristics for Hierarchical Directed Arc Routing ProblemsCode0
FORM: Learning Expressive and Transferable First-Order Logic Reward Machines—0
Towards Unraveling and Improving Generalization in World Models—0
Weber-Fechner Law in Temporal Difference learning derived from Control as Inference—0
Isoperimetry is All We Need: Langevin Posterior Sampling for RL with Sublinear Regret—0
An Unsupervised Anomaly Detection in Electricity Consumption Using Reinforcement Learning and Time Series Forest Based Framework—0
UnrealZoo: Enriching Photo-realistic Virtual Worlds for Embodied AI—0
Dynamic Optimization of Storage Systems Using Reinforcement Learning Techniques—0
Exploiting Hybrid Policy in Reinforcement Learning for Interpretable Temporal Logic ManipulationCode1
Enhancing Code LLMs with Reinforcement Learning in Code Generation: A Survey—0
Goal-Conditioned Data Augmentation for Offline Reinforcement Learning—0
Election of Collaborators via Reinforcement Learning for Federated Brain Tumor Segmentation—0
Efficient and Scalable Deep Reinforcement Learning for Mean Field Control GamesCode0
Graph-attention-based Casual Discovery with Trust Region-navigated Clipping Policy Optimization—0
Minimal Batch Adaptive Learning Policy Engine for Real-Time Mid-Price Forecasting in High-Frequency Trading—0
Preventive Energy Management for Distribution Systems Under Uncertain Events: A Deep Reinforcement Learning Approach—0
Provably Efficient Exploration in Reward Machines with Low Regret—0
Optimizing Fantasy Sports Team Selection with Deep Reinforcement Learning—0
A Reinforcement Learning-Based Task Mapping Method to Improve the Reliability of Clustered Manycores—0
xSRL: Safety-Aware Explainable Reinforcement Learning -- Safety as a Product of ExplainabilityCode0
Show:102550
← PrevPage 45 of 605Next →

Benchmark Results

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