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 13201–13250 of 15113 papers

TitleStatusHype
The Pump Scheduling Problem: A Real-World Scenario for Reinforcement LearningCode0
Robust Inverse Reinforcement Learning under Transition Dynamics MismatchCode0
Reinforcement Learning Assisted Recursive QAOACode0
Robust Learning from Observation with Model MisspecificationCode0
Maximum Entropy Deep Inverse Reinforcement LearningCode0
Multi-Objective Deep Reinforcement LearningCode0
Reinforcement Learning Approach for Mapping Applications to Dataflow-Based Coarse-Grained Reconfigurable ArrayCode0
Planning to Learn: A Novel Algorithm for Active Learning during Model-Based PlanningCode0
Why People Skip Music? On Predicting Music Skips using Deep Reinforcement LearningCode0
Multimodal Sentiment Analysis with Word-Level Fusion and Reinforcement LearningCode0
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement LearningCode0
MM-R5: MultiModal Reasoning-Enhanced ReRanker via Reinforcement Learning for Document RetrievalCode0
Speeding up Reinforcement Learning-based Information Extraction Training using Asynchronous MethodsCode0
Metalearned Neural MemoryCode0
Planning the path with Reinforcement Learning: Optimal Robot Motion Planning in RoboCup Small Size League EnvironmentsCode0
Spiders Based on Anxiety: How Reinforcement Learning Can Deliver Desired User Experience in Virtual Reality Personalized Arachnophobia TreatmentCode0
Robust Offline Reinforcement learning with Heavy-Tailed RewardsCode0
Planning Multiple Epidemic Interventions with Reinforcement LearningCode0
Placeto: Learning Generalizable Device Placement Algorithms for Distributed Machine LearningCode0
Unsupervised Learning for Robust Fitting:A Reinforcement Learning ApproachCode0
Variational Recurrent Models for Solving Partially Observable Control TasksCode0
Low Emission Building Control with Zero-Shot Reinforcement LearningCode0
Robust On-Policy Sampling for Data-Efficient Policy Evaluation in Reinforcement LearningCode0
Modelling crypto markets by multi-agent reinforcement learningCode0
Robust optimal well control using an adaptive multi-grid reinforcement learning frameworkCode0
MAgent: A Many-Agent Reinforcement Learning Platform for Artificial Collective IntelligenceCode0
Variation-resistant Q-learning: Controlling and Utilizing Estimation Bias in Reinforcement Learning for Better PerformanceCode0
PixelRL: Fully Convolutional Network with Reinforcement Learning for Image ProcessingCode0
Robust Policy Optimization in Deep Reinforcement LearningCode0
PixelBrax: Learning Continuous Control from Pixels End-to-End on the GPUCode0
Pittsburgh Learning Classifier Systems for Explainable Reinforcement Learning: Comparing with XCSCode0
The Role of Deep Learning Regularizations on Actors in Offline RLCode0
Model Learning for Look-ahead Exploration in Continuous ControlCode0
PIPPS: Flexible Model-Based Policy Search Robust to the Curse of ChaosCode0
Unsupervised multi-latent space reinforcement learning framework for video summarization in ultrasound imagingCode0
PIMbot: Policy and Incentive Manipulation for Multi-Robot Reinforcement Learning in Social DilemmasCode0
Physics-Informed Model and Hybrid Planning for Efficient Dyna-Style Reinforcement LearningCode0
S-RL Toolbox: Environments, Datasets and Evaluation Metrics for State Representation LearningCode0
XCS as a reinforcement learning approach to automatic test case prioritizationCode0
Reinforcement Learning with Dual-Observation for General Video Game PlayingCode0
Robust Reinforcement Learning in Continuous Control Tasks with Uncertainty Set RegularizationCode0
Is Policy Learning Overrated?: Width-Based Planning and Active Learning for AtariCode0
Robust Reinforcement Learning Objectives for Sequential Recommender SystemsCode0
SSR-Zero: Simple Self-Rewarding Reinforcement Learning for Machine TranslationCode0
Reinforcement Learning Approaches for Traffic Signal Control under Missing DataCode0
Physically Embedded Planning Problems: New Challenges for Reinforcement LearningCode0
Stabilising viscous extensional flows using Reinforcement LearningCode0
Robust Reinforcement Learning Under Minimax Regret for Green SecurityCode0
Robust Reinforcement Learning under model misspecificationCode0
Reinforcement Learning and Deep Learning based Lateral Control for Autonomous DrivingCode0
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Benchmark Results

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