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 11151–11175 of 15113 papers

TitleStatusHype
Two-stage training algorithm for AI robot soccer—0
Two-Step Reinforcement Learning for Multistage Strategy Card Game—0
UAS Navigation in the Real World Using Visual Observation—0
UAS Visual Navigation in Large and Unseen Environments via a Meta Agent—0
UAV aided Metaverse over Wireless Communications: A Reinforcement Learning Approach—0
UAV Aided Search and Rescue Operation Using Reinforcement Learning—0
UAV-Assisted Coverage Hole Detection Using Reinforcement Learning in Urban Cellular Networks—0
UAV-Assisted Enhanced Coverage and Capacity in Dynamic MU-mMIMO IoT Systems: A Deep Reinforcement Learning Approach—0
UAV-assisted Semantic Communication with Hybrid Action Reinforcement Learning—0
UAV Base Station Trajectory Optimization Based on Reinforcement Learning in Post-disaster Search and Rescue Operations—0
UAV Path Planning Employing MPC- Reinforcement Learning Method Considering Collision Avoidance—0
UAV Trajectory Planning in Wireless Sensor Networks for Energy Consumption Minimization by Deep Reinforcement Learning—0
UbuntuWorld 1.0 LTS - A Platform for Automated Problem Solving & Troubleshooting in the Ubuntu OS—0
UCB Exploration via Q-Ensembles—0
UDQL: Bridging The Gap between MSE Loss and The Optimal Value Function in Offline Reinforcement Learning—0
UDUC: An Uncertainty-driven Approach for Learning-based Robust Control—0
UIShift: Enhancing VLM-based GUI Agents through Self-supervised Reinforcement Learning—0
ULTHO: Ultra-Lightweight yet Efficient Hyperparameter Optimization in Deep Reinforcement Learning—0
Ultimate Intelligence Part III: Measures of Intelligence, Perception and Intelligent Agents—0
Ultrafast photonic reinforcement learning based on laser chaos—0
UMBRELLA: Uncertainty-Aware Model-Based Offline Reinforcement Learning Leveraging Planning—0
Unbiased Asymmetric Reinforcement Learning under Partial Observability—0
Unbiased Deep Reinforcement Learning: A General Training Framework for Existing and Future Algorithms—0
Unbiased learning with State-Conditioned Rewards in Adversarial Imitation Learning—0
Unbiased Methods for Multi-Goal Reinforcement Learning—0
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Benchmark Results

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