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 1851–1875 of 15113 papers

TitleStatusHype
Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement LearningCode1
GAEA: Graph Augmentation for Equitable Access via Reinforcement LearningCode1
Galactic: Scaling End-to-End Reinforcement Learning for Rearrangement at 100k Steps-Per-SecondCode1
Gamma and Vega Hedging Using Deep Distributional Reinforcement LearningCode1
A Benchmark Environment for Offline Reinforcement Learning in Racing GamesCode1
Gaussian RAM: Lightweight Image Classification via Stochastic Retina-Inspired Glimpse and Reinforcement LearningCode1
Generalising Discrete Action Spaces with Conditional Action TreesCode1
Generalizable Episodic Memory for Deep Reinforcement LearningCode1
Improving and Benchmarking Offline Reinforcement Learning AlgorithmsCode1
Generalization in Reinforcement Learning by Soft Data AugmentationCode1
Digital Twin-Enhanced Wireless Indoor Navigation: Achieving Efficient Environment Sensing with Zero-Shot Reinforcement LearningCode1
RLET: A Reinforcement Learning Based Approach for Explainable QA with Entailment TreesCode1
Distributional Soft Actor-Critic: Off-Policy Reinforcement Learning for Addressing Value Estimation ErrorsCode1
An Efficient Asynchronous Method for Integrating Evolutionary and Gradient-based Policy SearchCode1
AutoPhase: Juggling HLS Phase Orderings in Random Forests with Deep Reinforcement LearningCode1
AutoPhoto: Aesthetic Photo Capture using Reinforcement LearningCode1
Dual RL: Unification and New Methods for Reinforcement and Imitation LearningCode1
RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-FoldCode1
Imitating Graph-Based Planning with Goal-Conditioned PoliciesCode1
rl_reach: Reproducible Reinforcement Learning Experiments for Robotic Reaching TasksCode1
Benchmarking Reinforcement Learning Techniques for Autonomous NavigationCode1
Imitation Learning via Off-Policy Distribution MatchingCode1
Generalized Decision Transformer for Offline Hindsight Information MatchingCode1
Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from PixelsCode1
Image Classification by Reinforcement Learning with Two-State Q-LearningCode1
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Benchmark Results

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