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 9026–9050 of 15113 papers

TitleStatusHype
Reinforcement Learning Based Oscillation Dampening: Scaling up Single-Agent RL algorithms to a 100 AV highway field operational test—0
Reinforcement learning based parameters adaption method for particle swarm optimization—0
Reinforcement Learning based Path Exploration for Sequential Explainable Recommendation—0
Reinforcement Learning based Per-antenna Discrete Power Control for Massive MIMO Systems—0
Reinforcement Learning-Based Policy Optimisation For Heterogeneous Radio Access—0
Reinforcement Learning Based Power Grid Day-Ahead Planning and AI-Assisted Control—0
Reinforcement Learning Based Prediction of PID Controller Gains for Quadrotor UAVs—0
Reinforcement Learning based Proactive Control for Transmission Grid Resilience to Wildfire—0
Reinforcement Learning-based Product Delivery Frequency Control—0
Reinforcement Learning Based Query Vertex Ordering Model for Subgraph Matching—0
Reinforcement Learning based Recommender System using Biclustering Technique—0
Reinforcement learning based recommender systems: A survey—0
Reinforcement Learning-based Recommender Systems with Large Language Models for State Reward and Action Modeling—0
Reinforcement Learning Based Resource Allocation for Network Slices in O-RAN Midhaul—0
Reinforcement Learning Based Safe Decision Making for Highway Autonomous Driving—0
Reinforcement Learning Based Self-play and State Stacking Techniques for Noisy Air Combat Environment—0
Reinforcement Learning based Sequential Batch-sampling for Bayesian Optimal Experimental Design—0
Reinforcement Learning Based Sparse Black-box Adversarial Attack on Video Recognition Models—0
Reinforcement Learning Based Speech Enhancement for Robust Speech Recognition—0
Reinforcement Learning Based Text Style Transfer without Parallel Training Corpus—0
Reinforcement Learning-based Thermal Comfort Control for Vehicle Cabins—0
Reinforcement Learning-Based Trajectory Design for the Aerial Base Stations—0
Reinforcement Learning Based User-Guided Motion Planning for Human-Robot Collaboration—0
Reinforcement-Learning-Based Variational Quantum Circuits Optimization for Combinatorial Problems—0
Reinforcement Learning Based Vehicle-cell Association Algorithm for Highly Mobile Millimeter Wave Communication—0
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Benchmark Results

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