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 751–775 of 15113 papers

TitleStatusHype
Revealing higher-order neural representations of uncertainty with the Noise Estimation through Reinforcement-based Diffusion (NERD) model—0
Med-R1: Reinforcement Learning for Generalizable Medical Reasoning in Vision-Language ModelsCode2
Enhancing LLM Reasoning with Iterative DPO: A Comprehensive Empirical InvestigationCode1
APF+: Boosting adaptive-potential function reinforcement learning methods with a W-shaped network for high-dimensional games—0
Synchronous vs Asynchronous Reinforcement Learning in a Real World Robot—0
FLEX: A Framework for Learning Robot-Agnostic Force-based Skills Involving Sustained Contact Object Manipulation—0
A Reinforcement Learning-Driven Transformer GAN for Molecular Generation—0
Dynamic Angle Selection in X-Ray CT: A Reinforcement Learning Approach to Optimal Stopping—0
TERL: Large-Scale Multi-Target Encirclement Using Transformer-Enhanced Reinforcement LearningCode1
Evaluation-Time Policy Switching for Offline Reinforcement Learning—0
Sketch-to-Skill: Bootstrapping Robot Learning with Human Drawn Trajectory Sketches—0
Towards Better Alignment: Training Diffusion Models with Reinforcement Learning Against Sparse RewardsCode2
Adaptive Torque Control of Exoskeletons under Spasticity Conditions via Reinforcement Learning—0
Learning to reset in target search problemsCode0
Reinforcement Learning-Based Controlled Switching Approach for Inrush Current Minimization in Power Transformers—0
Exploring Competitive and Collusive Behaviors in Algorithmic Pricing with Deep Reinforcement Learning—0
Dynamic Obstacle Avoidance with Bounded Rationality Adversarial Reinforcement Learning—0
Reinforcement Learning Outperforms Supervised Fine-Tuning: A Case Study on Audio Question AnsweringCode3
Scalable Evaluation of Online Facilitation Strategies via Synthetic Simulation of DiscussionsCode0
Representation-based Reward Modeling for Efficient Safety Alignment of Large Language Model—0
Safe Continual Domain Adaptation after Sim2Real Transfer of Reinforcement Learning Policies in Robotics—0
SortingEnv: An Extendable RL-Environment for an Industrial Sorting Process—0
SySLLM: Generating Synthesized Policy Summaries for Reinforcement Learning Agents Using Large Language Models—0
H2-MARL: Multi-Agent Reinforcement Learning for Pareto Optimality in Hospital Capacity Strain and Human Mobility during Epidemic—0
DeepSeek-Inspired Exploration of RL-based LLMs and Synergy with Wireless Networks: A Survey—0
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Benchmark Results

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