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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 9001–9050 of 15113 papers

TitleStatusHype
Stochastic Approximation of Gaussian Free Energy for Risk-Sensitive Reinforcement Learning—0
Reinforcement learning for instance segmentation with high-level priors—0
Multi-Agent Deep Reinforcement Learning using Attentive Graph Neural Architectures for Real-Time Strategy Games—0
Techniques Toward Optimizing Viewability in RTB Ad Campaigns Using Reinforcement Learning—0
Revisiting Design Choices in Offline Model Based Reinforcement Learning—0
On Instrumental Variable Regression for Deep Offline Policy EvaluationCode0
RLIRank: Learning to Rank with Reinforcement Learning for Dynamic Search—0
On the use of feature-maps and parameter control for improved quality-diversity meta-evolution—0
Meta Reinforcement Learning for Fast Adaptation of Hierarchical Policies—0
Reinforcement Learning based Disease Progression Model for Alzheimer’s Disease—0
Objective-aware Traffic Simulation via Inverse Reinforcement Learning—0
Towards a Sample Efficient Reinforcement Learning Pipeline for Vision Based Robotics—0
Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning—0
A Stochastic Composite Augmented Lagrangian Method For Reinforcement Learning—0
Deep Reinforcement Learning for Optimal Stopping with Application in Financial EngineeringCode0
Learn Fine-grained Adaptive Loss for Multiple Anatomical Landmark Detection in Medical Images—0
Robo-Advising: Enhancing Investment with Inverse Optimization and Deep Reinforcement Learning—0
Online Adaptive Optimal Control Algorithm Based on Synchronous Integral Reinforcement Learning With Explorations—0
Reinforcement Learning Assisted Oxygen Therapy for COVID-19 Patients Under Intensive Care—0
Online Multimodal Transportation Planning using Deep Reinforcement Learning—0
Reinforcement Learning for Adaptive Video Compressive Sensing—0
Reinforcement Learning With Sparse-Executing Actions via Sparsity Regularization—0
Meta-Reinforcement Learning by Tracking Task Non-stationarityCode0
Sublinear Least-Squares Value Iteration via Locality Sensitive Hashing—0
PoBRL: Optimizing Multi-Document Summarization by Blending Reinforcement Learning Policies—0
Application of deep reinforcement learning for Indian stock trading automation—0
Learning and Information in Stochastic Networks and Queues—0
Gym-ANM: Open-source software to leverage reinforcement learning for power system management in research and education—0
Adaptive ABAC Policy Learning: A Reinforcement Learning Approach—0
Behavior-based Neuroevolutionary Training in Reinforcement LearningCode0
Generic Itemset Mining Based on Reinforcement LearningCode0
Mean Field Games Flock! The Reinforcement Learning Way—0
RL-GRIT: Reinforcement Learning for Grammar Inference—0
RAIDER: Reinforcement-aided Spear Phishing Detector—0
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting—0
Model-Based Offline Planning with Trajectory PruningCode0
DRAS-CQSim: A Reinforcement Learning based Framework for HPC Cluster Scheduling—0
Regret Minimization Experience Replay in Off-Policy Reinforcement LearningCode0
Ordering-Based Causal Discovery with Reinforcement Learning—0
Non-decreasing Quantile Function Network with Efficient Exploration for Distributional Reinforcement Learning—0
A Heuristically Assisted Deep Reinforcement Learning Approach for Network Slice Placement—0
Efficient PAC Reinforcement Learning in Regular Decision Processes—0
Feature-Based Interpretable Reinforcement Learning based on State-Transition Models—0
Adaptive Warm-Start MCTS in AlphaZero-like Deep Reinforcement Learning—0
Intelligence and Unambitiousness Using Algorithmic Information Theory—0
Online Algorithms and Policies Using Adaptive and Machine Learning Approaches—0
SIDE: State Inference for Partially Observable Cooperative Multi-Agent Reinforcement Learning—0
Reinforcement Learning Based Safe Decision Making for Highway Autonomous Driving—0
Principled Exploration via Optimistic Bootstrapping and Backward InductionCode0
Interpretable performance analysis towards offline reinforcement learning: A dataset perspective—0
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Benchmark Results

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