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
Challenging common bolus advisor for self-monitoring type-I diabetes patients using Reinforcement LearningCode0
Bridging the Imitation Gap by Adaptive Insubordination0
Reinforcement Learning with Fast Stabilization in Linear Dynamical Systems0
Adaptive Traffic Control with Deep Reinforcement Learning:Towards State-of-the-art and BeyondCode0
Buffer Pool Aware Query Scheduling via Deep Reinforcement Learning0
On the Convergence of Reinforcement Learning with Monte Carlo Exploring Starts0
Soft Expert Reward Learning for Vision-and-Language Navigation0
Multi-agent Reinforcement Learning in Bayesian Stackelberg Markov Games for Adaptive Moving Target Defense0
Lagrangian Duality in Reinforcement Learning0
A Short Note on Soft-max and Policy Gradients in Bandits Problems0
A Machine Learning Approach for Task and Resource Allocation in Mobile Edge Computing Based Networks0
Interpretable Control by Reinforcement Learning0
An Overview of Natural Language State Representation for Reinforcement Learning0
CATCH: Context-based Meta Reinforcement Learning for Transferrable Architecture Search0
Quick Question: Interrupting Users for Microtasks with Reinforcement Learning0
Structure Mapping for Transferability of Causal ModelsCode0
Hyperparameter Selection for Offline Reinforcement Learning0
Hierarchical Deep Reinforcement Learning Approach for Multi-Objective Scheduling With Varying Queue Sizes0
Dueling Deep Q Network for Highway Decision Making in Autonomous Vehicles: A Case Study0
CoNES: Convex Natural Evolutionary Strategies0
Human-like Energy Management Based on Deep Reinforcement Learning and Historical Driving Experiences0
Collision Avoidance Robotics Via Meta-Learning (CARML)Code0
Decision-making Strategy on Highway for Autonomous Vehicles using Deep Reinforcement Learning0
Distributed Reinforcement Learning of Targeted Grasping with Active Vision for Mobile Manipulators0
DRIFT: Deep Reinforcement Learning for Functional Software Testing0
Transfer Deep Reinforcement Learning-enabled Energy Management Strategy for Hybrid Tracked Vehicle0
Transferred Energy Management Strategies for Hybrid Electric Vehicles Based on Driving Conditions Recognition0
Meta-Gradient Reinforcement Learning with an Objective Discovered Online0
Reinforcement Learning-Enabled Decision-Making Strategies for a Vehicle-Cyber-Physical-System in Connected Environment0
Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity0
Qgraph-bounded Q-learning: Stabilizing Model-Free Off-Policy Deep Reinforcement Learning0
Computation Offloading in Beyond 5G Networks: A Distributed Learning Framework and Applications0
Deep PQR: Solving Inverse Reinforcement Learning using Anchor ActionsCode0
Information Freshness-Aware Task Offloading in Air-Ground Integrated Edge Computing Systems0
Inverse Reinforcement Learning from a Gradient-based Learner0
Learning to Sample with Local and Global Contexts in Experience Replay Buffer0
Robustifying Reinforcement Learning Agents via Action Space Adversarial Training0
Single-partition adaptive Q-learningCode0
Optimizing Memory Placement using Evolutionary Graph Reinforcement Learning0
Revisiting Fundamentals of Experience ReplayCode0
Reinforcement Learning of Musculoskeletal Control from Functional SimulationsCode0
AirCapRL: Autonomous Aerial Human Motion Capture using Deep Reinforcement Learning0
A Provably Efficient Sample Collection Strategy for Reinforcement Learning0
Adversarial jamming attacks and defense strategies via adaptive deep reinforcement learning0
Learning Abstract Models for Strategic Exploration and Fast Reward Transfer0
Relational-Grid-World: A Novel Relational Reasoning Environment and An Agent Model for Relational Information Extraction0
Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Approaches0
XCS as a reinforcement learning approach to automatic test case prioritizationCode0
Simulating multi-exit evacuation using deep reinforcement learning0
Investigation of Sentiment Controllable Chatbot0
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Benchmark Results

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