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 8626–8650 of 15113 papers

TitleStatusHype
Reinforcement Learning, Bit by Bit—0
Visual Explanation using Attention Mechanism in Actor-Critic-based Deep Reinforcement Learning—0
Asymptotic Theory for IV-Based Reinforcement Learning with Potential Endogeneity—0
Deep reinforcement learning in medical imaging: A literature review—0
Learning Collision-free and Torque-limited Robot Trajectories based on Alternative Safe BehaviorsCode1
A Dual-Memory Architecture for Reinforcement Learning on Neuromorphic Platforms—0
Automatic Exploration Process Adjustment for Safe Reinforcement Learning with Joint Chance Constraint Satisfaction—0
DeepFreight: Integrating Deep Reinforcement Learning and Mixed Integer Programming for Multi-transfer Truck Freight DeliveryCode1
MAMBPO: Sample-efficient multi-robot reinforcement learning using learned world modelsCode1
Routing algorithms as tools for integrating social distancing with emergency evacuation—0
Lyapunov-Regularized Reinforcement Learning for Power System Transient StabilityCode1
Unsupervised Learning for Robust Fitting:A Reinforcement Learning ApproachCode0
Two-step reinforcement learning for model-free redesign of nonlinear optimal regulatorCode0
Conservative Optimistic Policy Optimization via Multiple Importance SamplingCode0
Inverse Reinforcement Learning with Explicit Policy Estimates—0
Continuous Coordination As a Realistic Scenario for Lifelong LearningCode1
An RL-Based Adaptive Detection Strategy to Secure Cyber-Physical Systems—0
Improving Computational Efficiency in Visual Reinforcement Learning via Stored EmbeddingsCode1
Learning the Next Best View for 3D Point Clouds via Topological FeaturesCode1
Neuromechanics-based Deep Reinforcement Learning of Neurostimulation Control in FES cycling—0
Reinforcement Learning for Orientation Estimation Using Inertial Sensors with Performance Guarantee—0
Shape-driven Coordinate Ordering for Star Glyph Sets via Reinforcement Learning—0
Reinforcement Learning with External Knowledge by using Logical Neural Networks—0
Efficient UAV Trajectory-Planning using Economic Reinforcement Learning—0
Learning to Fly -- a Gym Environment with PyBullet Physics for Reinforcement Learning of Multi-agent Quadcopter ControlCode2
Show:102550
← PrevPage 346 of 605Next →

Benchmark Results

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