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 2701–2725 of 15113 papers

TitleStatusHype
Integrated Drill Boom Hole-Seeking Control via Reinforcement Learning—0
Foundations for Transfer in Reinforcement Learning: A Taxonomy of Knowledge Modalities—0
Self-Critical Alternate Learning based Semantic Broadcast Communication—0
Learning Curricula in Open-Ended Worlds—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
Tracking Object Positions in Reinforcement Learning: A Metric for Keypoint Detection (extended version)Code0
Age-Based Scheduling for Mobile Edge Computing: A Deep Reinforcement Learning ApproachCode1
Safe Reinforcement Learning in Tensor Reproducing Kernel Hilbert Space—0
Efficient Off-Policy Safe Reinforcement Learning Using Trust Region Conditional Value at Risk—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
Unveiling the Implicit Toxicity in Large Language ModelsCode1
Reinforcement Replaces Supervision: Query focused Summarization using Deep Reinforcement LearningCode0
Two-Step Reinforcement Learning for Multistage Strategy Card Game—0
Q-learning Based Optimal False Data Injection Attack on Probabilistic Boolean Control Networks—0
Safe Reinforcement Learning in a Simulated Robotic Arm—0
Two-step dynamic obstacle avoidanceCode0
An Investigation of Time Reversal Symmetry in Reinforcement LearningCode0
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Benchmark Results

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