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 1151–1175 of 15113 papers

TitleStatusHype
AnyBipe: An End-to-End Framework for Training and Deploying Bipedal Robots Guided by Large Language ModelsCode1
Contrastive Preference Learning: Learning from Human Feedback without RLCode1
SUBER: An RL Environment with Simulated Human Behavior for Recommender SystemsCode1
Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RLCode1
Contrastive Variational Reinforcement Learning for Complex ObservationsCode1
Controlgym: Large-Scale Control Environments for Benchmarking Reinforcement Learning AlgorithmsCode1
Controlling the Risk of Conversational Search via Reinforcement LearningCode1
Control-Oriented Model-Based Reinforcement Learning with Implicit DifferentiationCode1
Confidence Estimation Transformer for Long-term Renewable Energy Forecasting in Reinforcement Learning-based Power Grid DispatchingCode1
Connecting Deep-Reinforcement-Learning-based Obstacle Avoidance with Conventional Global Planners using Waypoint GeneratorsCode1
A Deep Reinforcement Learning Framework for the Financial Portfolio Management ProblemCode1
COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction EstimationCode1
CompoSuite: A Compositional Reinforcement Learning BenchmarkCode1
CoRL: Environment Creation and Management Focused on System IntegrationCode1
Compositional Reinforcement Learning from Logical SpecificationsCode1
Compound AI Systems Optimization: A Survey of Methods, Challenges, and Future DirectionsCode1
Critic-Guided Decoding for Controlled Text GenerationCode1
Critic Regularized RegressionCode1
CropGym: a Reinforcement Learning Environment for Crop ManagementCode1
Cross-Domain Policy Adaptation by Capturing Representation MismatchCode1
An Open-Source Multi-Goal Reinforcement Learning Environment for Robotic Manipulation with PybulletCode1
Cross-Modal Domain Adaptation for Reinforcement LearningCode1
Cross Modality 3D Navigation Using Reinforcement Learning and Neural Style TransferCode1
CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and SimplicityCode1
An Inductive Bias for Distances: Neural Nets that Respect the Triangle InequalityCode1
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Benchmark Results

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