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 4601–4625 of 15113 papers

TitleStatusHype
Safe Model-Based Reinforcement Learning with an Uncertainty-Aware Reachability CertificateCode1
Adaptive patch foraging in deep reinforcement learning agents—0
Query Rewriting for Effective Misinformation Discovery—0
Abstract-to-Executable Trajectory Translation for One-Shot Task GeneralizationCode1
Distributional Reward Estimation for Effective Multi-Agent Deep Reinforcement LearningCode0
A Reinforcement Learning Approach to Estimating Long-term Treatment Effects—0
Frame Mining: a Free Lunch for Learning Robotic Manipulation from 3D Point CloudsCode1
A Scalable Finite Difference Method for Deep Reinforcement Learning—0
Just Round: Quantized Observation Spaces Enable Memory Efficient Learning of Dynamic LocomotionCode0
Deep reinforcement learning for automatic run-time adaptation of UWB PHY radio settings—0
A Concise Introduction to Reinforcement Learning in Robotics—0
Harfang3D Dog-Fight Sandbox: A Reinforcement Learning Research Platform for the Customized Control Tasks of Fighter AircraftsCode2
Bootstrap Advantage Estimation for Policy Optimization in Reinforcement LearningCode0
Reinforcement Learning with Unbiased Policy Evaluation and Linear Function Approximation—0
Object-Category Aware Reinforcement Learning—0
Visual Reinforcement Learning with Self-Supervised 3D RepresentationsCode1
Personalized Federated Hypernetworks for Privacy Preservation in Multi-Task Reinforcement Learning—0
Towards Multi-Agent Reinforcement Learning driven Over-The-Counter Market Simulations—0
Policy Gradient With Serial Markov Chain Reasoning—0
Optimal Control of Material Micro-Structures—0
Multi-agent Dynamic Algorithm ConfigurationCode1
Sustainable Online Reinforcement Learning for Auto-biddingCode1
Towards Trustworthy Automatic Diagnosis Systems by Emulating Doctors' Reasoning with Deep Reinforcement LearningCode1
Observed Adversaries in Deep Reinforcement Learning—0
Output Feedback Adaptive Optimal Control of Affine Nonlinear systems with a Linear Measurement Model—0
Show:102550
← PrevPage 185 of 605Next →

Benchmark Results

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