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 5451–5475 of 15113 papers

TitleStatusHype
Robotic Lever Manipulation using Hindsight Experience Replay and Shapley Additive Explanations—0
Robotic Offline RL from Internet Videos via Value-Function Pre-Training—0
Robotic Search & Rescue via Online Multi-task Reinforcement Learning—0
Robotic self-representation improves manipulation skills and transfer learning—0
Robotic Table Tennis with Model-Free Reinforcement Learning—0
Robotic Table Wiping via Reinforcement Learning and Whole-body Trajectory Optimization—0
Robotic Tracking Control with Kernel Trick-based Reinforcement Learning—0
Robot in a China Shop: Using Reinforcement Learning for Location-Specific Navigation Behaviour—0
Robot Learning of Mobile Manipulation with Reachability Behavior Priors—0
Robot Navigation with Reinforcement Learned Path Generation and Fine-Tuned Motion Control—0
Robot path planning using deep reinforcement learning—0
Robot Policy Learning from Demonstration Using Advantage Weighting and Early Termination—0
Robot Representation and Reasoning with Knowledge from Reinforcement Learning—0
Robots and Children that Learn Together : Improving Knowledge Retention by Teaching Peer-Like Interactive Robots—0
Robot See, Robot Do: Imitation Reward for Noisy Financial Environments—0
Robot Sound Interpretation: Combining Sight and Sound in Learning-Based Control—0
Robust Action Governor for Uncertain Piecewise Affine Systems with Non-convex Constraints and Safe Reinforcement Learning—0
Robust Adversarial Attacks Detection based on Explainable Deep Reinforcement Learning For UAV Guidance and Planning—0
Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula—0
Robust Algorithmic Collusion—0
Robust Android Malware Detection System against Adversarial Attacks using Q-Learning—0
Robust and Scalable Routing with Multi-Agent Deep Reinforcement Learning for MANETs—0
Robust and Versatile Bipedal Jumping Control through Reinforcement Learning—0
Robusta: Robust AutoML for Feature Selection via Reinforcement Learning—0
Robust Auto-landing Control of an agile Regional Jet Using Fuzzy Q-learning—0
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Benchmark Results

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