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 2701–2750 of 15113 papers

TitleStatusHype
Foundations for Transfer in Reinforcement Learning: A Taxonomy of Knowledge Modalities—0
Integrated Drill Boom Hole-Seeking Control via Reinforcement Learning—0
Learning Curricula in Open-Ended Worlds—0
Self-Critical Alternate Learning based Semantic Broadcast Communication—0
BenchMARL: Benchmarking Multi-Agent Reinforcement Learning—0
A Multifidelity Sim-to-Real Pipeline for Verifiable and Compositional Reinforcement Learning—0
A Survey of Temporal Credit Assignment in Deep Reinforcement Learning—0
Harnessing Discrete Representations For Continual Reinforcement LearningCode1
DDxT: Deep Generative Transformer Models for Differential DiagnosisCode0
Age-Based Scheduling for Mobile Edge Computing: A Deep Reinforcement Learning ApproachCode1
Tracking Object Positions in Reinforcement Learning: A Metric for Keypoint Detection (extended version)Code0
Efficient Off-Policy Safe Reinforcement Learning Using Trust Region Conditional Value at Risk—0
Safe Reinforcement Learning in Tensor Reproducing Kernel Hilbert Space—0
Optimal Attack and Defense for Reinforcement LearningCode0
Data-efficient Deep Reinforcement Learning for Vehicle Trajectory Control—0
Predictable Reinforcement Learning Dynamics through Entropy Rate MinimizationCode0
Controlgym: Large-Scale Control Environments for Benchmarking Reinforcement Learning AlgorithmsCode1
Self-Driving Telescopes: Autonomous Scheduling of Astronomical Observation Campaigns with Offline Reinforcement Learning—0
Q-learning Based Optimal False Data Injection Attack on Probabilistic Boolean Control Networks—0
Reinforcement Replaces Supervision: Query focused Summarization using Deep Reinforcement LearningCode0
Unveiling the Implicit Toxicity in Large Language ModelsCode1
Two-Step Reinforcement Learning for Multistage Strategy Card Game—0
Safe Reinforcement Learning in a Simulated Robotic Arm—0
Two-step dynamic obstacle avoidanceCode0
An Investigation of Time Reversal Symmetry in Reinforcement LearningCode0
Temporal Transfer Learning for Traffic Optimization with Coarse-grained Advisory Autonomy—0
Optimal Observer Design Using Reinforcement Learning and Quadratic Neural Networks—0
A Graph Neural Network-Based QUBO-Formulated Hamiltonian-Inspired Loss Function for Combinatorial Optimization using Reinforcement Learning—0
Replay across Experiments: A Natural Extension of Off-Policy RL—0
A Fully Data-Driven Approach for Realistic Traffic Signal Control Using Offline Reinforcement Learning—0
Generative Modelling of Stochastic Actions with Arbitrary Constraints in Reinforcement LearningCode0
A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation—0
Margin Trader: A Reinforcement Learning Framework for Portfolio Management with Margin and ConstraintsCode0
Projected Off-Policy Q-Learning (POP-QL) for Stabilizing Offline Reinforcement Learning—0
Digital Twin-Native AI-Driven Service Architecture for Industrial Networks—0
Evaluating Pretrained models for Deployable Lifelong Learning—0
Risk-sensitive Markov Decision Process and Learning under General Utility Functions—0
Large Language Model as a Policy Teacher for Training Reinforcement Learning AgentsCode1
Learning to Fly in SecondsCode2
Probabilistic Inference in Reinforcement Learning Done Right—0
From Images to Connections: Can DQN with GNNs learn the Strategic Game of Hex?Code0
Analyzing Behaviors of Mixed Traffic via Reinforcement Learning at Unsignalized Intersections—0
Resilient Control of Networked Microgrids using Vertical Federated Reinforcement Learning: Designs and Real-Time Test-Bed Validations—0
Clustered Policy Decision Ranking—0
Reinforcement Learning and Deep Stochastic Optimal Control for Final Quadratic Hedging—0
Provably Efficient CVaR RL in Low-rank MDPs—0
Tactile Active Inference Reinforcement Learning for Efficient Robotic Manipulation Skill Acquisition—0
Offline Reinforcement Learning for Wireless Network Optimization with Mixture Datasets—0
Benchmarking Feature Extractors for Reinforcement Learning-Based Semiconductor Defect Localization—0
Imagination-Augmented Hierarchical Reinforcement Learning for Safe and Interactive Autonomous Driving in Urban Environments—0
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Benchmark Results

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