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 11951–12000 of 15113 papers

TitleStatusHype
Multi-step Greedy Reinforcement Learning Algorithms—0
Multi-Agent Reinforcement Learning for Order-dispatching via Order-Vehicle Distribution Matching—0
Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning?—0
Biased Aggregation, Rollout, and Enhanced Policy Improvement for Reinforcement Learning—0
Probabilistic Successor Representations with Kalman Temporal Differences—0
Attention-based Fault-tolerant Approach for Multi-agent Reinforcement Learning Systems—0
Discounted Reinforcement Learning Is Not an Optimization Problem—0
DeepMNavigate: Deep Reinforced Multi-Robot Navigation Unifying Local & Global Collision Avoidance—0
I'm sorry Dave, I'm afraid I can't do that, Deep Q-learning from forbidden action—0
Manufacturing Dispatching using Reinforcement and Transfer Learning—0
Zero Shot Learning on Simulated Robots—0
Using Logical Specifications of Objectives in Multi-Objective Reinforcement Learning—0
SensorDrop: A Reinforcement Learning Framework for Communication Overhead Reduction on the Edge—0
Reducing Overestimation Bias in Multi-Agent Domains Using Double Centralized CriticsCode0
Machine learning strategies for path-planning microswimmers in turbulent flows—0
Hybrid Zero Dynamics Inspired Feedback Control Policy Design for 3D Bipedal Locomotion using Reinforcement Learning—0
Review of Learning-based Longitudinal Motion Planning for Autonomous Vehicles: Research Gaps between Self-driving and Traffic Congestion—0
AI Assisted Annotator using Reinforcement Learning—0
CWAE-IRL: Formulating a supervised approach to Inverse Reinforcement Learning problem—0
Deep Reinforcement Learning for Single-Shot Diagnosis and Adaptation in Damaged Robots—0
Never Worse, Mostly Better: Stable Policy Improvement in Deep Reinforcement Learning—0
QuaRL: Quantization for Fast and Environmentally Sustainable Reinforcement LearningCode0
Relationship Explainable Multi-objective Optimization Via Vector Value Function Based Reinforcement Learning—0
Language is Power: Representing States Using Natural Language in Reinforcement Learning—0
SME-Net: Sparse Motion Estimation for Parametric Video Prediction Through Reinforcement LearningCode0
Reinforcement Learning for Multi-Objective Optimization of Online Decisions in High-Dimensional Systems—0
Machine Translation for Machines: the Sentiment Classification Use Case—0
Quantile QT-Opt for Risk-Aware Vision-Based Robotic Grasping—0
Fair Loss: Margin-Aware Reinforcement Learning for Deep Face Recognition—0
Deep Reinforcement Active Learning for Human-in-the-Loop Person Re-Identification—0
Generalization in Generation: A closer look at Exposure Bias—0
Generating Paraphrases with Lean Vocabulary—0
MGHRL: Meta Goal-generation for Hierarchical Reinforcement Learning—0
Dynamic Interaction-Aware Scene Understanding for Reinforcement Learning in Autonomous Driving—0
End-to-End Motion Planning of Quadrotors Using Deep Reinforcement Learning—0
RLCache: Automated Cache Management Using Reinforcement Learning—0
Tensor-based Cooperative Control for Large Scale Multi-intersection Traffic Signal Using Deep Reinforcement Learning and Imitation Learning—0
Multiagent Rollout Algorithms and Reinforcement LearningCode0
MULTIPOLAR: Multi-Source Policy Aggregation for Transfer Reinforcement Learning between Diverse Environmental DynamicsCode0
Relational Graph Learning for Crowd NavigationCode0
Accelerating the Computation of UCB and Related Indices for Reinforcement Learning—0
Deep Coordination GraphsCode0
Interaction-Aware Multi-Agent Reinforcement Learning for Mobile Agents with Individual Goals—0
Deep Reinforcement Learning Based Power control for Wireless Multicast Systems—0
Adaptive ROI Generation for Video Object Segmentation Using Reinforcement LearningCode0
Playing Atari Ball Games with Hierarchical Reinforcement Learning—0
Safe Reinforcement Learning on Autonomous Vehicles—0
SURREAL-System: Fully-Integrated Stack for Distributed Deep Reinforcement Learning—0
Relationship Explainable Multi-objective Reinforcement Learning with Semantic Explainability Generation—0
Towards a Metric for Automated Conversational Dialogue System Evaluation and Improvement—0
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Benchmark Results

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