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 3501–3550 of 15113 papers

TitleStatusHype
Deep Reinforcement Learning, a textbook—0
Deep Reinforcement Learning Aided Monte Carlo Tree Search for MIMO Detection—0
Deep Reinforcement Learning Aided Platoon Control Relying on V2X Information—0
Deep Reinforcement Learning-Aided RAN Slicing Enforcement for B5G Latency Sensitive Services—0
Automated Hybrid Reward Scheduling via Large Language Models for Robotic Skill Learning—0
Deep Reinforcement Learning amidst Lifelong Non-Stationarity—0
Deep Reinforcement Learning and Transportation Research: A Comprehensive Review—0
Deep Reinforcement Learning and Convex Mean-Variance Optimisation for Portfolio Management—0
Deep Reinforcement Learning and its Neuroscientific Implications—0
Deep Reinforcement Learning and Permissioned Blockchain for Content Caching in Vehicular Edge Computing and Networks—0
Deep Reinforcement Learning and the Deadly Triad—0
Automated Lane Change Strategy using Proximal Policy Optimization-based Deep Reinforcement Learning—0
Deep Reinforcement Learning: An Overview—0
Deep Reinforcement Learning Approach for Trading Automation in The Stock Market—0
Redefining Counterfactual Explanations for Reinforcement Learning: Overview, Challenges and Opportunities—0
Deep Reinforcement Learning Assisted Federated Learning Algorithm for Data Management of IIoT—0
Deep Reinforcement Learning Attention Selection for Person Re-Identification—0
A Structure-aware Online Learning Algorithm for Markov Decision Processes—0
AdaCoT: Pareto-Optimal Adaptive Chain-of-Thought Triggering via Reinforcement Learning—0
Demand response for residential building heating: Effective Monte Carlo Tree Search control based on physics-informed neural networks—0
Deep Reinforcement Learning Based Multidimensional Resource Management for Energy Harvesting Cognitive NOMA Communications—0
Adversarial Deep Reinforcement Learning based Adaptive Moving Target Defense—0
Deep Reinforcement Learning-Based Adaptive IRS Control with Limited Feedback Codebooks—0
Deep Reinforcement Learning-based Anti-jamming Power Allocation in a Two-cell NOMA Network—0
Deep Reinforcement Learning-based Authentic Dialogue Generation To Protect Youth From Cybergrooming—0
Deep Reinforcement Learning-Based Beam Tracking for Low-Latency Services in Vehicular Networks—0
Deep Reinforcement Learning based Blind mmWave MIMO Beam Alignment—0
Deep Reinforcement Learning-Based Channel Allocation for Wireless LANs with Graph Convolutional Networks—0
Deep Reinforcement Learning Based Controller for Active Heave Compensation—0
Deep Reinforcement Learning Based Dynamic Trajectory Control for UAV-assisted Mobile Edge Computing—0
Deep Reinforcement Learning Based Dynamic Route Planning for Minimizing Travel Time—0
Deep Reinforcement Learning based Dynamic Optimization of Bus Timetable—0
Counterfactual Explanation Policies in RL—0
PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback—0
A Strong Baseline for Batch Imitation Learning—0
Counterfactual Credit Assignment in Model-Free Reinforcement Learning—0
Deep Reinforcement Learning-based Image Captioning with Embedding Reward—0
Deep reinforcement learning-based image classification achieves perfect testing set accuracy for MRI brain tumors with a training set of only 30 images—0
A physics-informed reinforcement learning approach for the interfacial area transport in two-phase flow—0
Deep Reinforcement Learning Based Mobile Edge Computing for Intelligent Internet of Things—0
Deep Reinforcement Learning based Model-free On-line Dynamic Multi-Microgrid Formation to Enhance Resilience—0
Deep Reinforcement Learning Based Multi-Access Edge Computing Schedule for Internet of Vehicle—0
Agent based modelling for continuously varying supply chains—0
Deep Reinforcement Learning Based on Location-Aware Imitation Environment for RIS-Aided mmWave MIMO Systems—0
Accelerating the Computation of UCB and Related Indices for Reinforcement Learning—0
Deep Reinforcement Learning based Optimal Control of Hot Water Systems—0
Demand Responsive Dynamic Pricing Framework for Prosumer Dominated Microgrids using Multiagent Reinforcement Learning—0
A Stochastic Composite Augmented Lagrangian Method For Reinforcement Learning—0
Count-Based Temperature Scheduling for Maximum Entropy Reinforcement Learning—0
Delegative Reinforcement Learning: learning to avoid traps with a little help—0
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Benchmark Results

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