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 3201–3250 of 15113 papers

TitleStatusHype
PickLLM: Context-Aware RL-Assisted Large Language Model Routing—0
Ask1: Development and Reinforcement Learning-Based Control of a Custom Quadruped Robot—0
Coarse-to-Fine: A Dual-Phase Channel-Adaptive Method for Wireless Image Transmission—0
Latent Safety-Constrained Policy Approach for Safe Offline Reinforcement LearningCode0
Progressive-Resolution Policy Distillation: Leveraging Coarse-Resolution Simulations for Time-Efficient Fine-Resolution Policy Learning—0
Optimizing Sensor Redundancy in Sequential Decision-Making Problems—0
Mobile-TeleVision: Predictive Motion Priors for Humanoid Whole-Body Control—0
Swarm Behavior Cloning—0
Preference Adaptive and Sequential Text-to-Image Generation—0
Policy Agnostic RL: Offline RL and Online RL Fine-Tuning of Any Class and Backbone—0
Skill-Enhanced Reinforcement Learning Acceleration from Demonstrations—0
Unraveling the Complexity of Memory in RL Agents: an Approach for Classification and Evaluation—0
Mean--Variance Portfolio Selection by Continuous-Time Reinforcement Learning: Algorithms, Regret Analysis, and Empirical Study—0
Reinforcement Learning for a Discrete-Time Linear-Quadratic Control Problem with an Application—0
Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories—0
AI Planning: A Primer and Survey (Preliminary Report)—0
RLZero: Direct Policy Inference from Language Without In-Domain Supervision—0
ELEMENT: Episodic and Lifelong Exploration via Maximum Entropy—0
Finer Behavioral Foundation Models via Auto-Regressive Features and Advantage Weighting—0
Marvel: Accelerating Safe Online Reinforcement Learning with Finetuned Offline PolicyCode0
Traffic Co-Simulation Framework Empowered by Infrastructure Camera Sensing and Reinforcement Learning—0
Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning—0
Using Deep Reinforcement Learning to Enhance Channel Sampling Patterns in Integrated Sensing and Communication—0
Learning Whole-Body Loco-Manipulation for Omni-Directional Task Space Pose Tracking with a Wheeled-Quadrupedal-Manipulator—0
Learning on One Mode: Addressing Multi-Modality in Offline Reinforcement LearningCode0
Out-of-Distribution Detection for Neurosymbolic Autonomous Cyber Agents—0
AI-Driven Resource Allocation Framework for Microservices in Hybrid Cloud Platforms—0
Technical Report on Reinforcement Learning Control on the Lucas-Nülle Inverted Pendulum—0
Generating Critical Scenarios for Testing Automated Driving Systems—0
Reinforcement learning to learn quantum states for Heisenberg scaling accuracyCode0
Selective Reviews of Bandit Problems in AI via a Statistical View—0
A Memory-Based Reinforcement Learning Approach to Integrated Sensing and Communication—0
Dense Dynamics-Aware Reward Synthesis: Integrating Prior Experience with Demonstrations—0
Explore Reinforced: Equilibrium Approximation with Reinforcement Learning—0
Approximately Optimal Search on a Higher-dimensional Sliding PuzzleCode0
RL2: Reinforce Large Language Model to Assist Safe Reinforcement Learning for Energy Management of Active Distribution Networks—0
Provable Partially Observable Reinforcement Learning with Privileged Information—0
Bilinear Convolution Decomposition for Causal RL Interpretability—0
BOTS: Batch Bayesian Optimization of Extended Thompson Sampling for Severely Episode-Limited RL Settings—0
HVAC-DPT: A Decision Pretrained Transformer for HVAC Control—0
Solving Rubik's Cube Without Tricky Sampling—0
RL-MILP Solver: A Reinforcement Learning Approach for Solving Mixed-Integer Linear Programs with Graph Neural Networks—0
TEA: Trajectory Encoding Augmentation for Robust and Transferable Policies in Offline Reinforcement Learning—0
Convex Regularization and Convergence of Policy Gradient Flows under Safety Constraints—0
A Comprehensive Survey of Reinforcement Learning: From Algorithms to Practical Challenges—0
Supervised Learning-enhanced Multi-Group Actor Critic for Live Stream Allocation in FeedCode0
NeoHebbian Synapses to Accelerate Online Training of Neuromorphic Hardware—0
Dynamic Non-Prehensile Object Transport via Model-Predictive Reinforcement Learning—0
ScaleViz: Scaling Visualization Recommendation Models on Large Data—0
ELEMENTAL: Interactive Learning from Demonstrations and Vision-Language Models for Reward Design in Robotics—0
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Benchmark Results

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