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 1801–1850 of 15113 papers

TitleStatusHype
Comparing Popular Simulation Environments in the Scope of Robotics and Reinforcement LearningCode1
Quality Diversity through Human Feedback: Towards Open-Ended Diversity-Driven OptimizationCode1
Automatic Truss Design with Reinforcement LearningCode1
Quantum Architecture Search via Deep Reinforcement LearningCode1
Compiler Optimization for Quantum Computing Using Reinforcement LearningCode1
Q-value Regularized Transformer for Offline Reinforcement LearningCode1
Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative TasksCode1
Automating DBSCAN via Deep Reinforcement LearningCode1
AutoPhoto: Aesthetic Photo Capture using Reinforcement LearningCode1
Comparing Observation and Action Representations for Deep Reinforcement Learning in μRTSCode1
Compile Scene Graphs with Reinforcement LearningCode1
Confidence Estimation Transformer for Long-term Renewable Energy Forecasting in Reinforcement Learning-based Power Grid DispatchingCode1
Consistency Models as a Rich and Efficient Policy Class for Reinforcement LearningCode1
Randomized Exploration for Reinforcement Learning with General Value Function ApproximationCode1
Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced DatasetsCode1
Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement LearningCode1
RealAnt: An Open-Source Low-Cost Quadruped for Education and Research in Real-World Reinforcement LearningCode1
Real-time Bidding Strategy in Display Advertising: An Empirical AnalysisCode1
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
Reinforcement Learning for Combining Search Methods in the Calibration of Economic ABMsCode1
Combining Reinforcement Learning with Lin-Kernighan-Helsgaun Algorithm for the Traveling Salesman ProblemCode1
Combining Reinforcement Learning and Constraint Programming for Combinatorial OptimizationCode1
Recurrent Off-policy Baselines for Memory-based Continuous ControlCode1
Redeeming Intrinsic Rewards via Constrained OptimizationCode1
Reduced Policy Optimization for Continuous Control with Hard ConstraintsCode1
Combining Reinforcement Learning with Model Predictive Control for On-Ramp MergingCode1
Regulatory DNA sequence Design with Reinforcement LearningCode1
Autonomous Exploration Under Uncertainty via Deep Reinforcement Learning on GraphsCode1
Reinforced Epidemic Control: Saving Both Lives and EconomyCode1
Reinforcement Learning and Control as Probabilistic Inference: Tutorial and ReviewCode1
Reinforcement Learning and Tree Search Methods for the Unit Commitment ProblemCode1
Reinforcement Learning as One Big Sequence Modeling ProblemCode1
Reinforcement Learning-Based Automatic Berthing SystemCode1
Combining Semantic Guidance and Deep Reinforcement Learning For Generating Human Level PaintingsCode1
Reinforcement Learning-based Model Predictive Control for Greenhouse Climate ControlCode1
Reinforcement Learning-based Non-Autoregressive Solver for Traveling Salesman ProblemsCode1
Reinforcement Learning-based Placement of Charging Stations in Urban Road NetworksCode1
Reinforcement Learning Enhanced Quantum-inspired Algorithm for Combinatorial OptimizationCode1
Reinforcement Learning for Abstractive Question Summarization with Question-aware Semantic RewardsCode1
Reinforcement Learning for Ballbot Navigation in Uneven TerrainCode1
Reinforcement Learning for Branch-and-Bound Optimisation using Retrospective TrajectoriesCode1
Reinforcement Learning for Dynamic Resource Allocation in Optical Networks: Hype or Hope?Code1
Reinforcement learning for Energies of the future and carbon neutrality: a Challenge DesignCode1
Combining Deep Reinforcement Learning and Search for Imperfect-Information GamesCode1
Reinforcement Learning for Low-Thrust Trajectory Design of Interplanetary MissionsCode1
Combinatorial Optimization with Policy Adaptation using Latent Space SearchCode1
AMAGO: Scalable In-Context Reinforcement Learning for Adaptive AgentsCode1
Reinforcement Learning for Adaptive Optimal Stationary Control of Linear Stochastic SystemsCode1
Learning to combine primitive skills: A step towards versatile robotic manipulationCode1
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Benchmark Results

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