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 8601–8650 of 15113 papers

TitleStatusHype
Challenges for Reinforcement Learning in Healthcare—0
A Scavenger Hunt for Service RobotsCode0
I am Robot: Neuromuscular Reinforcement Learning to Actuate Human Limbs through Functional Electrical Stimulation—0
Decentralized Circle Formation Control for Fish-like Robots in the Real-world via Reinforcement Learning—0
A Learning-Based Computational Impact Time Guidance—0
Increasing Energy Efficiency of Massive-MIMO Network via Base Stations Switching using Reinforcement Learning and Radio Environment Maps—0
An Energy-Saving Snake Locomotion Gait Policy Obtained Using Deep Reinforcement Learning—0
A Taxonomy of Similarity Metrics for Markov Decision Processes—0
A multi-agent reinforcement learning model of reputation and cooperation in human groups—0
Adversarial Reinforcement Learning for Procedural Content Generation—0
Behavior From the Void: Unsupervised Active Pre-TrainingCode1
Distributed Reinforcement Learning for Flexible and Efficient UAV Swarm Control—0
Instabilities of Offline RL with Pre-Trained Neural Representation—0
Comparing Popular Simulation Environments in the Scope of Robotics and Reinforcement LearningCode1
A Crash Course on Reinforcement LearningCode1
Vision-Based Mobile Robotics Obstacle Avoidance With Deep Reinforcement Learning—0
Provably Efficient Cooperative Multi-Agent Reinforcement Learning with Function Approximation—0
A Reinforcement Learning Based R-Tree for Spatial Data Indexing in Dynamic Environments—0
Latent Imagination Facilitates Zero-Shot Transfer in Autonomous RacingCode1
Real-world Ride-hailing Vehicle Repositioning using Deep Reinforcement Learning—0
Markov Cricket: Using Forward and Inverse Reinforcement Learning to Model, Predict And Optimize Batting Performance in One-Day International Cricket—0
Learning Human Rewards by Inferring Their Latent Intelligence Levels in Multi-Agent Games: A Theory-of-Mind Approach with Application to Driving Data—0
A Lower Bound for the Sample Complexity of Inverse Reinforcement Learning—0
SAINT-ACC: Safety-Aware Intelligent Adaptive Cruise Control for Autonomous Vehicles Using Deep Reinforcement Learning—0
Passing Through Narrow Gaps with Deep Reinforcement Learning—0
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
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Benchmark Results

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