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 801–850 of 15113 papers

TitleStatusHype
Doubly Mild Generalization for Offline Reinforcement LearningCode1
Contingency-Aware Influence Maximization: A Reinforcement Learning ApproachCode1
Drama: Mamba-Enabled Model-Based Reinforcement Learning Is Sample and Parameter EfficientCode1
Dream and Search to Control: Latent Space Planning for Continuous ControlCode1
A Minimalist Approach to Offline Reinforcement LearningCode1
DreamerPro: Reconstruction-Free Model-Based Reinforcement Learning with Prototypical RepresentationsCode1
Constrained Update Projection Approach to Safe Policy OptimizationCode1
Constrained Policy Optimization via Bayesian World ModelsCode1
DrM: Mastering Visual Reinforcement Learning through Dormant Ratio MinimizationCode1
DROPO: Sim-to-Real Transfer with Offline Domain RandomizationCode1
DTR-Bench: An in silico Environment and Benchmark Platform for Reinforcement Learning Based Dynamic Treatment RegimeCode1
DUMP: Automated Distribution-Level Curriculum Learning for RL-based LLM Post-trainingCode1
Constrained Variational Policy Optimization for Safe Reinforcement LearningCode1
DxFormer: A Decoupled Automatic Diagnostic System Based on Decoder-Encoder Transformer with Dense Symptom RepresentationsCode1
Active Inference for Stochastic ControlCode1
Constrained episodic reinforcement learning in concave-convex and knapsack settingsCode1
Echo Chamber: RL Post-training Amplifies Behaviors Learned in PretrainingCode1
EDGE: Explaining Deep Reinforcement Learning PoliciesCode1
Effective Diversity in Population Based Reinforcement LearningCode1
Effective Multi-User Delay-Constrained Scheduling with Deep Recurrent Reinforcement LearningCode1
Efficient Active Search for Combinatorial Optimization ProblemsCode1
Efficient Adversarial Training without Attacking: Worst-Case-Aware Robust Reinforcement LearningCode1
Constraint-Guided Reinforcement Learning: Augmenting the Agent-Environment-InteractionCode1
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and PlanningCode1
AI2-THOR: An Interactive 3D Environment for Visual AICode1
Continual Backprop: Stochastic Gradient Descent with Persistent RandomnessCode1
Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement LearningCode1
Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning ApproachCode1
Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement LearningCode1
Efficient Risk-Averse Reinforcement LearningCode1
A Modular Framework for Reinforcement Learning Optimal ExecutionCode1
AI-Driven Day-to-Day Route ChoiceCode1
Conservative Q-Learning for Offline Reinforcement LearningCode1
Conservative Offline Distributional Reinforcement LearningCode1
Emergence of Locomotion Behaviours in Rich EnvironmentsCode1
Emergent behavior and neural dynamics in artificial agents tracking turbulent plumesCode1
Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement LearningCode1
Zero-Shot Reinforcement Learning from Low Quality DataCode1
Connecting Deep-Reinforcement-Learning-based Obstacle Avoidance with Conventional Global Planners using Waypoint GeneratorsCode1
Randomized Entity-wise Factorization for Multi-Agent Reinforcement LearningCode1
Energy-Based Imitation LearningCode1
Energy-Guided Diffusion Sampling for Offline-to-Online Reinforcement LearningCode1
ENERO: Efficient Real-Time WAN Routing Optimization with Deep Reinforcement LearningCode1
Enforcing Policy Feasibility Constraints through Differentiable Projection for Energy OptimizationCode1
Enhanced POET: Open-Ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their SolutionsCode1
Enhancement of a state-of-the-art RL-based detection algorithm for Massive MIMO radarsCode1
Conservative and Adaptive Penalty for Model-Based Safe Reinforcement LearningCode1
Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged FraudstersCode1
Reliable Conditioning of Behavioral Cloning for Offline Reinforcement LearningCode1
Confidence Estimation Transformer for Long-term Renewable Energy Forecasting in Reinforcement Learning-based Power Grid DispatchingCode1
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Benchmark Results

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