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 1551–1600 of 15113 papers

TitleStatusHype
Asynchronous Fractional Multi-Agent Deep Reinforcement Learning for Age-Minimal Mobile Edge Computing—0
Spiders Based on Anxiety: How Reinforcement Learning Can Deliver Desired User Experience in Virtual Reality Personalized Arachnophobia TreatmentCode0
Revisiting Space Mission Planning: A Reinforcement Learning-Guided Approach for Multi-Debris Rendezvous—0
Offline and Distributional Reinforcement Learning for Radio Resource Management—0
On-orbit Servicing for Spacecraft Collision Avoidance With Autonomous Decision Making—0
OffRIPP: Offline RL-based Informative Path Planning—0
Learning with Dynamics: Autonomous Regulation of UAV Based Communication Networks with Dynamic UAV Crew—0
Reinforcement Leaning for Infinite-Dimensional Systems—0
From Goal-Conditioned to Language-Conditioned Agents via Vision-Language Models—0
Whole-body End-Effector Pose Tracking—0
Stage-Wise Reward Shaping for Acrobatic Robots: A Constrained Multi-Objective Reinforcement Learning ApproachCode2
Development and Validation of Heparin Dosing Policies Using an Offline Reinforcement Learning Algorithm—0
Energy Saving in 6G O-RAN Using DQN-based xApp—0
Intelligent Routing Algorithm over SDN: Reusable Reinforcement Learning Approach—0
CANDERE-COACH: Reinforcement Learning from Noisy Feedback—0
Physics Enhanced Residual Policy Learning (PERPL) for safety cruising in mixed traffic platooning under actuator and communication delay—0
A novel agent with formal goal-reaching guarantees: an experimental study with a mobile robot—0
A Distribution-Aware Flow-Matching for Generating Unstructured Data for Few-Shot Reinforcement Learning—0
OMG-RL:Offline Model-based Guided Reward Learning for Heparin Treatment—0
Scalable Multi-agent Reinforcement Learning for Factory-wide Dynamic Scheduling—0
SoloParkour: Constrained Reinforcement Learning for Visual Locomotion from Privileged Experience—0
MAGICS: Adversarial RL with Minimax Actors Guided by Implicit Critic Stackelberg for Convergent Neural Synthesis of Robot Safety—0
Disentangling Recognition and Decision Regrets in Image-Based Reinforcement Learning—0
Reinforcement Learning-based Model Predictive Control for Greenhouse Climate ControlCode1
Training Language Models to Self-Correct via Reinforcement LearningCode2
Assessing the Zero-Shot Capabilities of LLMs for Action Evaluation in RL—0
TACO-RL: Task Aware Prompt Compression Optimization with Reinforcement Learning—0
The Central Role of the Loss Function in Reinforcement Learning—0
Reinforcement Learning as an Improvement Heuristic for Real-World Production Scheduling—0
Data-Efficient Quadratic Q-Learning Using LMIs—0
IMRL: Integrating Visual, Physical, Temporal, and Geometric Representations for Enhanced Food Acquisition—0
An Enhanced-State Reinforcement Learning Algorithm for Multi-Task Fusion in Large-Scale Recommender Systems—0
On-policy Actor-Critic Reinforcement Learning for Multi-UAV Exploration—0
A Reinforcement Learning Environment for Automatic Code Optimization in the MLIR Compiler—0
Leveraging Symmetry to Accelerate Learning of Trajectory Tracking Controllers for Free-Flying Robotic SystemsCode1
Mitigating Partial Observability in Adaptive Traffic Signal Control with Transformers—0
Logic Synthesis Optimization with Predictive Self-Supervision via Causal Transformers—0
Offline Reinforcement Learning for Learning to Dispatch for Job Shop SchedulingCode0
Instigating Cooperation among LLM Agents Using Adaptive Information Modulation—0
Enhancing RL Safety with Counterfactual LLM ReasoningCode1
Robust Reinforcement Learning with Dynamic Distortion Risk MeasuresCode0
Safety-Oriented Pruning and Interpretation of Reinforcement Learning Policies—0
An Offline Adaptation Framework for Constrained Multi-Objective Reinforcement Learning—0
Mitigating Dimensionality in 2D Rectangle Packing Problem under Reinforcement Learning Schema—0
KAN v.s. MLP for Offline Reinforcement Learning—0
PIP-Loco: A Proprioceptive Infinite Horizon Planning Framework for Quadrupedal Robot Locomotion—0
Average-Reward Maximum Entropy Reinforcement Learning for Underactuated Double Pendulum Tasks—0
Batch Ensemble for Variance Dependent Regret in Stochastic Bandits—0
CPL: Critical Plan Step Learning Boosts LLM Generalization in Reasoning Tasks—0
Quasimetric Value Functions with Dense Rewards—0
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Benchmark Results

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