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 9701–9725 of 15113 papers

TitleStatusHype
Deep Reinforcement Learning for Stabilization of Large-scale Probabilistic Boolean Networks—0
Deep Reinforcement Learning for Stochastic Computation Offloading in Digital Twin Networks—0
Deep Reinforcement Learning for Stock Portfolio Optimization—0
Deep Reinforcement Learning for System-on-Chip: Myths and Realities—0
Deep Reinforcement Learning for Task Offloading in UAV-Aided Smart Farm Networks—0
Selective Network Discovery via Deep Reinforcement Learning on Embedded Spaces—0
Deep Reinforcement Learning for Tensegrity Robot Locomotion—0
Deep Reinforcement Learning for the Design of Metamaterial Mechanisms with Functional Compliance Control—0
Deep Reinforcement Learning for Time Scheduling in RF-Powered Backscatter Cognitive Radio Networks—0
Deep Reinforcement Learning for Time Optimal Velocity Control using Prior Knowledge—0
Deep Reinforcement Learning for Trading—0
Deep Reinforcement Learning for Traffic Light Control in Intelligent Transportation Systems—0
Deep Reinforcement Learning for Unmanned Aerial Vehicle-Assisted Vehicular Networks—0
Deep Reinforcement Learning for Visual Object Tracking in Videos—0
Deep Reinforcement Learning for Weapons to Targets Assignment in a Hypersonic strike—0
Deep Reinforcement Learning for Resource Constrained Multiclass Scheduling in Wireless Networks—0
Deep Reinforcement Learning for Wireless Resource Allocation Using Buffer State Information—0
Deep Reinforcement Learning for Wireless Scheduling in Distributed Networked Control—0
Deep Reinforcement Learning: Framework, Applications, and Embedded Implementations—0
Deep Reinforcement Learning from Policy-Dependent Human Feedback—0
Deep Reinforcement Learning From Raw Pixels in Doom—0
Deep reinforcement learning guided graph neural networks for brain network analysis—0
Deep Reinforcement Learning in a Monetary Model—0
Deep Reinforcement Learning in Computer Vision: A Comprehensive Survey—0
Deep Reinforcement Learning in Cryptocurrency Market Making—0
Show:102550
← PrevPage 389 of 605Next →

Benchmark Results

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