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

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Showing 3651–3700 of 15113 papers

TitleStatusHype
Value of Information and Reward Specification in Active Inference and POMDPs—0
Introduction to Reinforcement Learning—0
Online Optimization of Curriculum Learning Schedules using Evolutionary Optimization—0
GFlowNet Training by Policy GradientsCode0
The Bandit Whisperer: Communication Learning for Restless Bandits—0
Optimizing Portfolio with Two-Sided Transactions and Lending: A Reinforcement Learning Framework—0
Hybrid Reinforcement Learning Breaks Sample Size Barriers in Linear MDPs—0
Deep Reinforcement Learning for the Design of Metamaterial Mechanisms with Functional Compliance Control—0
Deep Reinforcement Learning for Robotics: A Survey of Real-World Successes—0
Learning Rate-Free Reinforcement Learning: A Case for Model Selection with Non-Stationary ObjectivesCode0
PLANRL: A Motion Planning and Imitation Learning Framework to Bootstrap Reinforcement Learning—0
CADRL: Category-aware Dual-agent Reinforcement Learning for Explainable Recommendations over Knowledge Graphs—0
Integrating Controllable Motion Skills from Demonstrations—0
Model-free optimal controller for discrete-time Markovian jump linear systems: A Q-learning approach—0
Full error analysis of policy gradient learning algorithms for exploratory linear quadratic mean-field control problem in continuous time with common noise—0
Active Sensing of Knee Osteoarthritis Progression with Reinforcement Learning—0
Reinforcement Learning for an Efficient and Effective Malware Investigation during Cyber Incident Response—0
Coordinating Planning and Tracking in Layered Control Policies via Actor-Critic LearningCode0
Multi-Objective Deep Reinforcement Learning for Optimisation in Autonomous Systems—0
TCR-GPT: Integrating Autoregressive Model and Reinforcement Learning for T-Cell Receptor Repertoires Generation—0
A Survey on Self-play Methods in Reinforcement Learning—0
Adaptive Transit Signal Priority based on Deep Reinforcement Learning and Connected Vehicles in a Traffic Microsimulation Environment—0
On the Perturbed States for Transformed Input-robust Reinforcement LearningCode0
Multi-agent Assessment with QoS Enhancement for HD Map Updates in a Vehicular Network—0
Image-Based Deep Reinforcement Learning with Intrinsically Motivated Stimuli: On the Execution of Complex Robotic Tasks—0
ProSpec RL: Plan Ahead, then Execute—0
Towards Generalizable Reinforcement Learning via Causality-Guided Self-Adaptive Representations—0
A Method for Fast Autonomy Transfer in Reinforcement Learning—0
Appraisal-Guided Proximal Policy Optimization: Modeling Psychological Disorders in Dynamic Grid World—0
Evolution of cooperation in the public goods game with Q-learning—0
Anomalous State Sequence Modeling to Enhance Safety in Reinforcement Learning—0
Learning to Provably Satisfy High Relative Degree Constraints for Black-Box Systems—0
QT-TDM: Planning With Transformer Dynamics Model and Autoregressive Q-Learning—0
Reinforcement learning for anisotropic p-adaptation and error estimation in high-order solvers—0
Differentiable Quantum Architecture Search in Asynchronous Quantum Reinforcement Learning—0
SoNIC: Safe Social Navigation with Adaptive Conformal Inference and Constrained Reinforcement Learning—0
Path Following and Stabilisation of a Bicycle Model using a Reinforcement Learning Approach—0
Pretrained Visual Representations in Reinforcement Learning—0
Sublinear Regret for a Class of Continuous-Time Linear-Quadratic Reinforcement Learning Problems—0
From Imitation to Refinement -- Residual RL for Precise Assembly—0
Automatic Environment Shaping is the Next Frontier in RL—0
ODGR: Online Dynamic Goal Recognition—0
SECRM-2D: RL-Based Efficient and Comfortable Route-Following Autonomous Driving with Analytic Safety Guarantees—0
Functional Acceleration for Policy Mirror DescentCode0
Importance Sampling-Guided Meta-Training for Intelligent Agents in Highly Interactive Environments—0
Artificial Intelligence-based Decision Support Systems for Precision and Digital Health—0
Should we use model-free or model-based control? A case study of battery management systems—0
Concept-Based Interpretable Reinforcement Learning with Limited to No Human Labels—0
Comprehensive Overview of Reward Engineering and Shaping in Advancing Reinforcement Learning Applications—0
Offline Imitation Learning Through Graph Search and Retrieval—0
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Benchmark Results

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