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 5401–5425 of 15113 papers

TitleStatusHype
RLCorrector: Reinforced Proofreading for Cell-level Microscopy Image Segmentation—0
RL-CoSeg : A Novel Image Co-Segmentation Algorithm with Deep Reinforcement Learning—0
RL-CycleGAN: Reinforcement Learning Aware Simulation-To-Real—0
RL-DAUNCE: Reinforcement Learning-Driven Data Assimilation with Uncertainty-Aware Constrained Ensembles—0
RL-DistPrivacy: Privacy-Aware Distributed Deep Inference for low latency IoT systems—0
RL-Duet: Online Music Accompaniment Generation Using Deep Reinforcement Learning—0
RL-GA: A Reinforcement Learning-Based Genetic Algorithm for Electromagnetic Detection Satellite Scheduling Problem—0
R-learning in actor-critic model offers a biologically relevant mechanism for sequential decision-making—0
RLEEGNet: Integrating Brain-Computer Interfaces with Adaptive AI for Intuitive Responsiveness and High-Accuracy Motor Imagery Classification—0
RLeXplore: Accelerating Research in Intrinsically-Motivated Reinforcement Learning—0
RL for Consistency Models: Faster Reward Guided Text-to-Image Generation—0
RL-GPT: Integrating Reinforcement Learning and Code-as-policy—0
RL-GRIT: Reinforcement Learning for Grammar Inference—0
RL-Guided MPC for Autonomous Greenhouse Control—0
RLingua: Improving Reinforcement Learning Sample Efficiency in Robotic Manipulations With Large Language Models—0
RLINK: Deep Reinforcement Learning for User Identity Linkage—0
RLInspect: An Interactive Visual Approach to Assess Reinforcement Learning Algorithm—0
RLIRank: Learning to Rank with Reinforcement Learning for Dynamic Search—0
LIMIS: Locally Interpretable Modeling using Instance-wise Subsampling—0
RL-MD: A Novel Reinforcement Learning Approach for DNA Motif Discovery—0
RL-MILP Solver: A Reinforcement Learning Approach for Solving Mixed-Integer Linear Programs with Graph Neural Networks—0
RL + Model-based Control: Using On-demand Optimal Control to Learn Versatile Legged Locomotion—0
RL-MPCA: A Reinforcement Learning Based Multi-Phase Computation Allocation Approach for Recommender Systems—0
RLocator: Reinforcement Learning for Bug Localization—0
RLOC: Neurobiologically Inspired Hierarchical Reinforcement Learning Algorithm for Continuous Control of Nonlinear Dynamical Systems—0
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Benchmark Results

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