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 9651–9675 of 15113 papers

TitleStatusHype
Deep Reinforcement Learning for Multi-Truck Vehicle Routing Problems with Multi-Leg Demand Routes—0
Deep Reinforcement Learning for Multi-user Massive MIMO with Channel Aging—0
Deep Reinforcement Learning for Navigation in AAA Video Games—0
Deep Reinforcement Learning for Neural Control—0
Deep Reinforcement Learning for NLP—0
Deep Reinforcement Learning for On-line Dialogue State Tracking—0
DEAR: Deep Reinforcement Learning for Online Advertising Impression in Recommender Systems—0
Deep Reinforcement Learning for Online Control of Stochastic Partial Differential Equations—0
Deep Reinforcement Learning for Online Routing of Unmanned Aerial Vehicles with Wireless Power Transfer—0
Deep Reinforcement Learning for Online Error Detection in Cyber-Physical Systems—0
Deep reinforcement learning for optical systems: A case study of mode-locked lasers—0
Deep Reinforcement Learning for Optimal Control of Space Heating—0
Deep Reinforcement Learning for Optimal Critical Care Pain Management with Morphine using Dueling Double-Deep Q Networks—0
Deep Reinforcement Learning for Optimal Investment and Saving Strategy Selection in Heterogeneous Profiles: Intelligent Agents working towards retirement—0
Deep Reinforcement Learning for Optimal Power Flow with Renewables Using Graph Information—0
Deep reinforcement learning for optimal well control in subsurface systems with uncertain geology—0
Deep Reinforcement Learning for Optimizing RIS-Assisted HD-FD Wireless Systems—0
Deep Reinforcement Learning for Option Replication and Hedging—0
Deep Reinforcement Learning for Organ Localization in CT—0
Deep Reinforcement Learning for Orienteering Problems Based on Decomposition—0
Deep Reinforcement Learning for Page-wise Recommendations—0
Deep Reinforcement Learning for Personalized Search Story Recommendation—0
Deep Reinforcement Learning for Portfolio Optimization using Latent Feature State Space (LFSS) Module—0
Deep Reinforcement Learning for Power Control in Next-Generation WiFi Network Systems—0
Domain-adapted Learning and Imitation: DRL for Power Arbitrage—0
Show:102550
← PrevPage 387 of 605Next →

Benchmark Results

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