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

Showing 13511375 of 15113 papers

TitleStatusHype
Stackelberg Actor-Critic: Game-Theoretic Reinforcement Learning AlgorithmsCode1
NICE: Robust Scheduling through Reinforcement Learning-Guided Integer ProgrammingCode1
Pythia: A Customizable Hardware Prefetching Framework Using Online Reinforcement LearningCode1
The Role of Tactile Sensing in Learning and Deploying Grasp Refinement AlgorithmsCode1
Enhancing Navigational Safety in Crowded Environments using Semantic-Deep-Reinforcement-Learning-based NavigationCode1
Trust Region Policy Optimisation in Multi-Agent Reinforcement LearningCode1
A Workflow for Offline Model-Free Robotic Reinforcement LearningCode1
A Reinforcement Learning Benchmark for Autonomous Driving in Intersection ScenariosCode1
ENERO: Efficient Real-Time WAN Routing Optimization with Deep Reinforcement LearningCode1
AutoPhoto: Aesthetic Photo Capture using Reinforcement LearningCode1
Deep Policies for Online Bipartite Matching: A Reinforcement Learning ApproachCode1
Reinforcement Learning with Evolutionary Trajectory Generator: A General Approach for Quadrupedal LocomotionCode1
Learning to Navigate Intersections with Unsupervised Driver Trait InferenceCode1
Gradient Imitation Reinforcement Learning for Low Resource Relation ExtractionCode1
safe-control-gym: a Unified Benchmark Suite for Safe Learning-based Control and Reinforcement Learning in RoboticsCode1
Learning Selective Communication for Multi-Agent Path FindingCode1
TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph ForecastingCode1
PowerGym: A Reinforcement Learning Environment for Volt-Var Control in Power Distribution SystemsCode1
Optimizing Quantum Variational Circuits with Deep Reinforcement LearningCode1
WarpDrive: Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning on a GPUCode1
SurRoL: An Open-source Reinforcement Learning Centered and dVRK Compatible Platform for Surgical Robot LearningCode1
Hallucinated but Factual! Inspecting the Factuality of Hallucinations in Abstractive SummarizationCode1
Deep Reinforcement Learning at the Edge of the Statistical PrecipiceCode1
ReGen: Reinforcement Learning for Text and Knowledge Base Generation using Pretrained Language ModelsCode1
Active Inference for Stochastic ControlCode1
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Benchmark Results

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