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 10901–10950 of 15113 papers

TitleStatusHype
Balancing Reinforcement Learning Training Experiences in Interactive Information Retrieval—0
AutoHAS: Efficient Hyperparameter and Architecture Search—0
State Action Separable Reinforcement Learning—0
Refined Continuous Control of DDPG Actors via Parametrised Activation—0
Visual Transfer for Reinforcement Learning via Wasserstein Domain ConfusionCode0
Meta-Model-Based Meta-Policy Optimization—0
Constrained Reinforcement Learning for Dynamic Optimization under Uncertainty—0
A Novel Update Mechanism for Q-Networks Based On Extreme Learning MachinesCode0
Causality and Batch Reinforcement Learning: Complementary Approaches To Planning In Unknown Domains—0
Learning to Scan: A Deep Reinforcement Learning Approach for Personalized Scanning in CT Imaging—0
The Value-Improvement Path: Towards Better Representations for Reinforcement Learning—0
Temporally-Extended ε-Greedy ExplorationCode0
Diversity Actor-Critic: Sample-Aware Entropy Regularization for Sample-Efficient ExplorationCode0
Jointly Learning Environments and Control Policies with Projected Stochastic Gradient AscentCode0
Active Vision for Early Recognition of Human Actions—0
A novel approach for multi-agent cooperative pursuit to capture grouped evaders—0
Reinforcement learning and Bayesian data assimilation for model-informed precision dosing in oncology—0
Mitigating Bias in Face Recognition Using Skewness-Aware Reinforcement Learning—0
Temporal-Differential Learning in Continuous Environments—0
Robust Reinforcement Learning with Wasserstein Constraint—0
Model-Based Reinforcement Learning with Value-Targeted Regression—0
Variational Reward Estimator Bottleneck: Learning Robust Reward Estimator for Multi-Domain Task-Oriented Dialog—0
MM-KTD: Multiple Model Kalman Temporal Differences for Reinforcement LearningCode0
Reinforcement LearningCode0
AI-based Resource Allocation: Reinforcement Learning for Adaptive Auto-scaling in Serverless Environments—0
Domain Knowledge Integration By Gradient Matching For Sample-Efficient Reinforcement Learning—0
Intelligent Residential Energy Management System using Deep Reinforcement Learning—0
Revisiting Parameter Sharing in Multi-Agent Deep Reinforcement LearningCode0
Time-Variant Variational Transfer for Value Functions—0
Towards intervention-centric causal reasoning in learning agents—0
Anomaly Detection Under Controlled Sensing Using Actor-Critic Reinforcement Learning—0
A reinforcement learning approach to rare trajectory samplingCode0
ALBA : Reinforcement Learning for Video Object SegmentationCode0
Integrating LEO Satellite and UAV Relaying via Reinforcement Learning for Non-Terrestrial Networks—0
Active Measure Reinforcement Learning for Observation Cost Minimization—0
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model—0
Efficient Use of heuristics for accelerating XCS-based Policy Learning in Markov Games—0
Gradient Monitored Reinforcement Learning—0
Generator and Critic: A Deep Reinforcement Learning Approach for Slate Re-ranking in E-commerce—0
Dynamic Value Estimation for Single-Task Multi-Scene Reinforcement Learning—0
Deep Reinforcement Learning Based Power Allocation for D2D Network—0
Deep Learning Models for Automatic Summarization—0
Policy Entropy for Out-of-Distribution Classification—0
Optimization-driven Deep Reinforcement Learning for Robust Beamforming in IRS-assisted Wireless Communications—0
Meta-Reinforcement Learning for Trajectory Design in Wireless UAV Networks—0
Reinforcement Learning with Iterative Reasoning for Merging in Dense Traffic—0
Model-free Reinforcement Learning for Stochastic Stackelberg Security Games—0
GoChat: Goal-oriented Chatbots with Hierarchical Reinforcement Learning—0
Automatic Discovery of Interpretable Planning StrategiesCode0
Evaluating Generalisation in General Video Game Playing—0
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Benchmark Results

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