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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 731–740 of 15113 papers

Title	Date	Tasks	Status	Hype
Neural Inventory Control in Networks via Hindsight Differentiable Policy Optimization	Jun 20, 2023	Deep Reinforcement LearningManagement	CodeCode Available	1
PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning	Jun 19, 2023	reinforcement-learningReinforcement Learning (RL)	CodeCode Available	1
Galactic: Scaling End-to-End Reinforcement Learning for Rearrangement at 100k Steps-Per-Second	Jun 13, 2023	GPUReinforcement Learning (RL)	CodeCode Available	1
Transcendental Idealism of Planner: Evaluating Perception from Planning Perspective for Autonomous Driving	Jun 12, 2023	Autonomous DrivingAutonomous Vehicles	CodeCode Available	1
Policy Regularization with Dataset Constraint for Offline Reinforcement Learning	Jun 11, 2023	Offline RLreinforcement-learning	CodeCode Available	1
Digital Twin-Enhanced Wireless Indoor Navigation: Achieving Efficient Environment Sensing with Zero-Shot Reinforcement Learning	Jun 11, 2023	Navigatereinforcement-learning	CodeCode Available	1
An End-to-End Reinforcement Learning Approach for Job-Shop Scheduling Problems Based on Constraint Programming	Jun 9, 2023	Combinatorial OptimizationFeature Engineering	CodeCode Available	1
On the Importance of Feature Decorrelation for Unsupervised Representation Learning in Reinforcement Learning	Jun 9, 2023	Reinforcement Learning (RL)Representation Learning	CodeCode Available	1
Decoupled Prioritized Resampling for Offline RL	Jun 8, 2023	Offline RLReinforcement Learning (RL)	CodeCode Available	1
Look Beneath the Surface: Exploiting Fundamental Symmetry for Sample-Efficient Offline RL	Jun 7, 2023	Data AugmentationOffline RL	CodeCode Available	1

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Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	PPG	Mean Normalized Performance	0.76	—	Unverified
2	PPO	Mean Normalized Performance	0.58	—	Unverified