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

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Showing 651–700 of 15113 papers

TitleStatusHype
Reinforcement Learning with Maskable Stock Representation for Portfolio Management in Customizable Stock PoolsCode1
Reinforcement Learning with Model Predictive Control for Highway Ramp MeteringCode1
Direct Preference Optimization for Neural Machine Translation with Minimum Bayes Risk DecodingCode1
Combinatorial Optimization with Policy Adaptation using Latent Space SearchCode1
Accelerating Exploration with Unlabeled Prior DataCode1
Uni-O4: Unifying Online and Offline Deep Reinforcement Learning with Multi-Step On-Policy OptimizationCode1
State-Wise Safe Reinforcement Learning With Pixel ObservationsCode1
AlberDICE: Addressing Out-Of-Distribution Joint Actions in Offline Multi-Agent RL via Alternating Stationary Distribution Correction EstimationCode1
Hierarchical Reinforcement Learning for Power Network Topology ControlCode1
Unleashing the Power of Pre-trained Language Models for Offline Reinforcement LearningCode1
DrM: Mastering Visual Reinforcement Learning through Dormant Ratio MinimizationCode1
Variational Curriculum Reinforcement Learning for Unsupervised Discovery of SkillsCode1
Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement LearningCode1
CROP: Conservative Reward for Model-based Offline Policy OptimizationCode1
Safe Navigation: Training Autonomous Vehicles using Deep Reinforcement Learning in CARLACode1
Diversify Question Generation with Retrieval-Augmented Style TransferCode1
Contrastive Preference Learning: Learning from Human Feedback without RLCode1
Automatic Unit Test Data Generation and Actor-Critic Reinforcement Learning for Code SynthesisCode1
Vision-Language Models are Zero-Shot Reward Models for Reinforcement LearningCode1
Towards Robust Offline Reinforcement Learning under Diverse Data CorruptionCode1
Quality Diversity through Human Feedback: Towards Open-Ended Diversity-Driven OptimizationCode1
AMAGO: Scalable In-Context Reinforcement Learning for Adaptive AgentsCode1
Reduced Policy Optimization for Continuous Control with Hard ConstraintsCode1
METRA: Scalable Unsupervised RL with Metric-Aware AbstractionCode1
Offline Retraining for Online RL: Decoupled Policy Learning to Mitigate Exploration BiasCode1
Aligning Language Models with Human Preferences via a Bayesian ApproachCode1
Safe Deep Policy AdaptationCode1
GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning ModelsCode1
Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced DatasetsCode1
Self-Supervised Neuron Segmentation with Multi-Agent Reinforcement LearningCode1
Discovering General Reinforcement Learning Algorithms with Adversarial Environment DesignCode1
PGDQN: Preference-Guided Deep Q-NetworkCode1
Improving Planning with Large Language Models: A Modular Agentic ArchitectureCode1
Consistency Models as a Rich and Efficient Policy Class for Reinforcement LearningCode1
AdaRefiner: Refining Decisions of Language Models with Adaptive FeedbackCode1
Motif: Intrinsic Motivation from Artificial Intelligence FeedbackCode1
Zero-Shot Reinforcement Learning from Low Quality DataCode1
Recurrent Hypernetworks are Surprisingly Strong in Meta-RLCode1
Enhancing data efficiency in reinforcement learning: a novel imagination mechanism based on mesh information propagationCode1
KuaiSim: A Comprehensive Simulator for Recommender SystemsCode1
Physics-constrained robust learning of open-form partial differential equations from limited and noisy dataCode1
VAPOR: Legged Robot Navigation in Outdoor Vegetation Using Offline Reinforcement LearningCode1
Toward Discretization-Consistent Closure Schemes for Large Eddy Simulation Using Reinforcement LearningCode1
Reasoning with Latent Diffusion in Offline Reinforcement LearningCode1
Prompt to Transfer: Sim-to-Real Transfer for Traffic Signal Control with Prompt LearningCode1
Language Reward Modulation for Pretraining Reinforcement LearningCode1
Dialogue for Prompting: a Policy-Gradient-Based Discrete Prompt Generation for Few-shot LearningCode1
Reinforcement Learning for Financial Index TrackingCode1
ESRL: Efficient Sampling-based Reinforcement Learning for Sequence GenerationCode1
qgym: A Gym for Training and Benchmarking RL-Based Quantum CompilationCode1
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Benchmark Results

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