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 451–500 of 15113 papers

TitleStatusHype
ACN-Sim: An Open-Source Simulator for Data-Driven Electric Vehicle Charging ResearchCode1
A SWAT-based Reinforcement Learning Framework for Crop ManagementCode1
Curriculum Offline Imitation LearningCode1
D2RL: Deep Dense Architectures in Reinforcement LearningCode1
DARTS: Differentiable Architecture SearchCode1
Asynchronous Reinforcement Learning for Real-Time Control of Physical RobotsCode1
A Text-based Deep Reinforcement Learning Framework for Interactive RecommendationCode1
Data-Efficient Deep Reinforcement Learning for Attitude Control of Fixed-Wing UAVs: Field ExperimentsCode1
Debiased Contrastive LearningCode1
Deep Reinforcement Learning for List-wise RecommendationsCode1
Asset Allocation: From Markowitz to Deep Reinforcement LearningCode1
Attacking Cooperative Multi-Agent Reinforcement Learning by Adversarial Minority InfluenceCode1
A Benchmark Environment for Offline Reinforcement Learning in Racing GamesCode1
Ctrl-DNA: Controllable Cell-Type-Specific Regulatory DNA Design via Constrained RLCode1
Attractive or Faithful? Popularity-Reinforced Learning for Inspired Headline GenerationCode1
Debiasing Meta-Gradient Reinforcement Learning by Learning the Outer Value FunctionCode1
A Benchmark Environment Motivated by Industrial Control ProblemsCode1
Augmenting Policy Learning with Routines Discovered from a Single DemonstrationCode1
Augmenting Reinforcement Learning with Behavior Primitives for Diverse Manipulation TasksCode1
Augmenting Reinforcement Learning with Transformer-based Scene Representation Learning for Decision-making of Autonomous DrivingCode1
Decomposed Soft Actor-Critic Method for Cooperative Multi-Agent Reinforcement LearningCode1
A Closer Look at Advantage-Filtered Behavioral Cloning in High-Noise DatasetsCode1
Decoupling Value and Policy for Generalization in Reinforcement LearningCode1
Deep Active Inference for Partially Observable MDPsCode1
Automated Cloud Provisioning on AWS using Deep Reinforcement LearningCode1
Deep Deterministic Portfolio OptimizationCode1
Curiosity-Driven Energy-Efficient Worker Scheduling in Vehicular Crowdsourcing: A Deep Reinforcement Learning ApproachCode1
Deep Implicit Coordination Graphs for Multi-agent Reinforcement LearningCode1
Curious Hierarchical Actor-Critic Reinforcement LearningCode1
AutoPhase: Compiler Phase-Ordering for High Level Synthesis with Deep Reinforcement LearningCode1
DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character SkillsCode1
Adaptive Risk-Tendency: Nano Drone Navigation in Cluttered Environments with Distributional Reinforcement LearningCode1
Cryptocurrency Portfolio Management with Deep Reinforcement LearningCode1
Automatic Data Augmentation for Generalization in Deep Reinforcement LearningCode1
Automatic Data Augmentation for Generalization in Reinforcement LearningCode1
Deep Multi-agent Reinforcement Learning for Highway On-Ramp Merging in Mixed TrafficCode1
Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement LearningCode1
Automatic Truss Design with Reinforcement LearningCode1
Automating DBSCAN via Deep Reinforcement LearningCode1
Autonomous Exploration Under Uncertainty via Deep Reinforcement Learning on GraphsCode1
ABIDES-Gym: Gym Environments for Multi-Agent Discrete Event Simulation and Application to Financial MarketsCode1
Deep Reinforcement Learning based Evasion Generative Adversarial Network for Botnet DetectionCode1
Autonomous Reinforcement Learning: Formalism and BenchmarkingCode1
Autonomous Racing using a Hybrid Imitation-Reinforcement Learning ArchitectureCode1
When should we prefer Decision Transformers for Offline Reinforcement Learning?Code1
AutoPhase: Juggling HLS Phase Orderings in Random Forests with Deep Reinforcement LearningCode1
Avalon: A Benchmark for RL Generalization Using Procedurally Generated WorldsCode1
Deep Reinforcement Learning for Active Human Pose EstimationCode1
CTDS: Centralized Teacher with Decentralized Student for Multi-Agent Reinforcement LearningCode1
Ask Your Humans: Using Human Instructions to Improve Generalization in Reinforcement LearningCode1
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Benchmark Results

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