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 8976–9000 of 15113 papers

TitleStatusHype
Adaptive Optimal Control for Reference Tracking Independent of Exo-System Dynamics—0
Reinforcement learning-based adaptive speed controllers in mixed autonomy condition—0
Reinforcement Learning-based Admission Control in Delay-sensitive Service Systems—0
Reinforcement Learning based Air Combat Maneuver Generation—0
Reinforcement Learning-Based Air Traffic Deconfliction—0
Reinforcement Learning Based Algorithm for the Maximization of EV Charging Station Revenue—0
Reinforcement Learning Based Approaches to Adaptive Context Caching in Distributed Context Management Systems—0
Reinforcement Learning Based Argument Component Detection—0
Reinforcement Learning Based Asymmetrical DNN Modularization for Optimal Loading—0
Reinforcement learning Based Automated Design of Differential Evolution Algorithm for Black-box Optimization—0
Reinforcement Learning-based Automatic Diagnosis of Acute Appendicitis in Abdominal CT—0
Reinforcement Learning-based Application Autoscaling in the Cloud: A Survey—0
A Reinforcement Learning based approach for Multi-target Detection in Massive MIMO radar—0
Reinforcement Learning Based Bidding Framework with High-dimensional Bids in Power Markets—0
Reinforcement Learning-Based Bionic Reflex Control for Anthropomorphic Robotic Grasping exploiting Domain Randomization—0
Reinforcement Learning-based Black-Box Evasion Attacks to Link Prediction in Dynamic Graphs—0
Reinforcement Learning Based Character Controlling—0
Reinforcement Learning-Based Controlled Switching Approach for Inrush Current Minimization in Power Transformers—0
Reinforcement Learning-based Control of Nonlinear Systems using Carleman Approximation: Structured and Unstructured Designs—0
Reinforcement Learning Based Cooperative Coded Caching under Dynamic Popularities in Ultra-Dense Networks—0
Reinforcement Learning-Based Cooperative P2P Power Trading between DC Nanogrid Clusters with Wind and PV Energy Resources—0
Reinforcement Learning-Based Coverage Path Planning with Implicit Cellular Decomposition—0
Reinforcement Learning based Curriculum Optimization for Neural Machine Translation—0
Reinforcement Learning-based Defect Mitigation for Quality Assurance of Additive Manufacturing—0
Reinforcement Learning based Design of Linear Fixed Structure Controllers—0
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Benchmark Results

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