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 3176–3200 of 15113 papers

TitleStatusHype
Bayesian Critique-Tune-Based Reinforcement Learning with Adaptive Pressure for Multi-Intersection Traffic Signal Control—0
Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models—0
Harvesting energy from turbulent winds with Reinforcement Learning—0
Tilted Quantile Gradient Updates for Quantile-Constrained Reinforcement LearningCode0
Multi-Task Reinforcement Learning for Quadrotors—0
Learning Visuotactile Estimation and Control for Non-prehensile Manipulation under Occlusions—0
CLIP-RLDrive: Human-Aligned Autonomous Driving via CLIP-Based Reward Shaping in Reinforcement Learning—0
ParMod: A Parallel and Modular Framework for Learning Non-Markovian Tasks—0
Design of Restricted Normalizing Flow towards Arbitrary Stochastic Policy with Computational Efficiency—0
Using machine learning to inform harvest control rule design in complex fishery settingsCode0
Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation—0
Equivariant Action Sampling for Reinforcement Learning and Planning—0
Efficient Policy Adaptation with Contrastive Prompt Ensemble for Embodied Agents—0
MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization—0
MGDA: Model-based Goal Data Augmentation for Offline Goal-conditioned Weighted Supervised Learning—0
Adaptive Reward Design for Reinforcement LearningCode0
Automated Driving with Evolution Capability: A Reinforcement Learning Method with Monotonic Performance Enhancement—0
Continuous-time optimal investment with portfolio constraints: a reinforcement learning approach—0
Physics Instrument Design with Reinforcement Learning—0
Reward Machine Inference for Robotic Manipulation—0
Deep Reinforcement Learning for Scalable Multiagent Spacecraft Inspection—0
PickLLM: Context-Aware RL-Assisted Large Language Model Routing—0
Quantum-Train-Based Distributed Multi-Agent Reinforcement Learning—0
From Text to Trajectory: Exploring Complex Constraint Representation and Decomposition in Safe Reinforcement Learning—0
Reinforcement Learning Within the Classical Robotics Stack: A Case Study in Robot Soccer—0
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Benchmark Results

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