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 1060110650 of 15113 papers

TitleStatusHype
Decentralized Deep Reinforcement Learning for a Distributed and Adaptive Locomotion Controller of a Hexapod RobotCode1
Learning and Reasoning for Robot Dialog and Navigation Tasks0
Finite-sample Analysis of Greedy-GQ with Linear Function Approximation under Markovian Noise0
Deep Reinforcement Learning for High Level Character Control0
A reinforcement learning based decision support system in textile manufacturing process0
Reinforcement Learning for Variable Selection in a Branch and Bound Algorithm0
Mirror Descent Policy OptimizationCode1
Two-stage Deep Reinforcement Learning for Inverter-based Volt-VAR Control in Active Distribution Networks0
A Survey of Reinforcement Learning Algorithms for Dynamically Varying Environments0
Learning to Herd Agents Amongst Obstacles: Training Robust Shepherding Behaviors using Deep Reinforcement Learning0
Batch-Augmented Multi-Agent Reinforcement Learning for Efficient Traffic Signal Optimization0
Experience Augmentation: Boosting and Accelerating Off-Policy Multi-Agent Reinforcement Learning0
Human Instruction-Following with Deep Reinforcement Learning via Transfer-Learning from Text0
Reinforcement Learning for Caching with Space-Time Popularity Dynamics0
Ultrasound Video Summarization using Deep Reinforcement LearningCode1
Privileged Information Dropout in Reinforcement Learning0
Optimal Charging Method for Effective Li-ion Battery Life Extension Based on Reinforcement Learning0
Local and Global Explanations of Agent Behavior: Integrating Strategy Summaries with Saliency MapsCode0
Basal Glucose Control in Type 1 Diabetes using Deep Reinforcement Learning: An In Silico Validation0
Automating Turbulence Modeling by Multi-Agent Reinforcement Learning0
A Simple Imitation Learning Method via Contrastive Regularization0
Lifelong Control of Off-grid Microgrid with Model Based Reinforcement LearningCode1
Learning Transferable Concepts in Deep Reinforcement Learning0
A Distributional View on Multi-Objective Policy Optimization0
Think Too Fast Nor Too Slow: The Computational Trade-off Between Planning And Reinforcement LearningCode0
Data-driven Dynamic Multi-objective Optimal Control: An Aspiration-satisfying Reinforcement Learning Approach0
Context-aware Dynamics Model for Generalization in Model-Based Reinforcement LearningCode1
Solve Traveling Salesman Problem by Monte Carlo Tree Search and Deep Neural Network0
Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning0
Probabilistic Guarantees for Safe Deep Reinforcement Learning0
Proxy Experience Replay: Federated Distillation for Distributed Reinforcement Learning0
DREAM Architecture: a Developmental Approach to Open-Ended Learning in Robotics0
Explainable Reinforcement Learning: A Survey0
From Simulation to Real World Maneuver Execution using Deep Reinforcement Learning0
A New Deep Neural Architecture Search Pipeline for Face Recognition0
Unbiased Deep Reinforcement Learning: A General Training Framework for Existing and Future Algorithms0
MOReL : Model-Based Offline Reinforcement LearningCode1
Training spiking neural networks using reinforcement learningCode1
Planning to Explore via Self-Supervised World ModelsCode1
Smooth Exploration for Robotic Reinforcement LearningCode2
Reinforcement Learning Based on Real-Time Iteration NMPC0
Mobile Robot Path Planning in Dynamic Environments through Globally Guided Reinforcement LearningCode1
TOMA: Topological Map Abstraction for Reinforcement Learning0
Delay-Aware Multi-Agent Reinforcement Learning for Cooperative and Competitive EnvironmentsCode1
Delay-Aware Model-Based Reinforcement Learning for Continuous ControlCode1
A Deep Reinforcement Learning Approach to Efficient Drone Mobility Support0
Deep Reinforcement Learning for Organ Localization in CT0
Maximizing Information Gain in Partially Observable Environments via Prediction Reward0
Unified Models of Human Behavioral Agents in Bandits, Contextual Bandits and RLCode1
A Reinforcement Learning based approach for Multi-target Detection in Massive MIMO radar0
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Benchmark Results

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