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 851–900 of 15113 papers

TitleStatusHype
Asynchronous Multi-Agent Reinforcement Learning for Efficient Real-Time Multi-Robot Cooperative ExplorationCode1
Extreme Q-Learning: MaxEnt RL without EntropyCode1
Emergent collective intelligence from massive-agent cooperation and competitionCode1
Learning to Maximize Mutual Information for Dynamic Feature SelectionCode1
Goal-Guided Transformer-Enabled Reinforcement Learning for Efficient Autonomous NavigationCode1
Environment Agnostic Representation for Visual Reinforcement LearningCode1
Self-Activating Neural Ensembles for Continual Reinforcement LearningCode1
Transformer in Transformer as Backbone for Deep Reinforcement LearningCode1
Symbolic Visual Reinforcement Learning: A Scalable Framework with Object-Level Abstraction and Differentiable Expression SearchCode1
Risk-Sensitive Policy with Distributional Reinforcement LearningCode1
On Pathologies in KL-Regularized Reinforcement Learning from Expert DemonstrationsCode1
Lexicographic Multi-Objective Reinforcement LearningCode1
Example-guided learning of stochastic human driving policies using deep reinforcement learningCode1
On Reinforcement Learning for the Game of 2048Code1
Critic-Guided Decoding for Controlled Text GenerationCode1
Generating Multiple-Length Summaries via Reinforcement Learning for Unsupervised Sentence SummarizationCode1
Offline Reinforcement Learning for Visual NavigationCode1
Hybrid Multi-agent Deep Reinforcement Learning for Autonomous Mobility on Demand SystemsCode1
MoDem: Accelerating Visual Model-Based Reinforcement Learning with DemonstrationsCode1
Reinforcement Learning and Tree Search Methods for the Unit Commitment ProblemCode1
Targeted Adversarial Attacks on Deep Reinforcement Learning Policies via Model CheckingCode1
Compiler Optimization for Quantum Computing Using Reinforcement LearningCode1
PrefRec: Recommender Systems with Human Preferences for Reinforcing Long-term User EngagementCode1
Physics-Informed Model-Based Reinforcement LearningCode1
RLogist: Fast Observation Strategy on Whole-slide Images with Deep Reinforcement LearningCode1
MeshDQN: A Deep Reinforcement Learning Framework for Improving Meshes in Computational Fluid DynamicsCode1
Karolos: An Open-Source Reinforcement Learning Framework for Robot-Task EnvironmentsCode1
ConvLab-3: A Flexible Dialogue System Toolkit Based on a Unified Data FormatCode1
Efficient Reinforcement Learning Through Trajectory GenerationCode1
One Risk to Rule Them All: A Risk-Sensitive Perspective on Model-Based Offline Reinforcement LearningCode1
Real-time Bidding Strategy in Display Advertising: An Empirical AnalysisCode1
The Effectiveness of World Models for Continual Reinforcement LearningCode1
Improved Representation of Asymmetrical Distances with Interval Quasimetric EmbeddingsCode1
Quantile Constrained Reinforcement Learning: A Reinforcement Learning Framework Constraining Outage ProbabilityCode1
BEAR: Physics-Principled Building Environment for Control and Reinforcement LearningCode1
Masked Autoencoding for Scalable and Generalizable Decision MakingCode1
TEMPERA: Test-Time Prompting via Reinforcement LearningCode1
Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop SchedulingCode1
Efficient Meta Reinforcement Learning for Preference-based Fast AdaptationCode1
Let Offline RL Flow: Training Conservative Agents in the Latent Space of Normalizing FlowsCode1
Debiasing Meta-Gradient Reinforcement Learning by Learning the Outer Value FunctionCode1
LibSignal: An Open Library for Traffic Signal ControlCode1
Language-Conditioned Reinforcement Learning to Solve Misunderstandings with Action CorrectionsCode1
Towards Data-Driven Offline Simulations for Online Reinforcement LearningCode1
Redeeming Intrinsic Rewards via Constrained OptimizationCode1
Online Anomalous Subtrajectory Detection on Road Networks with Deep Reinforcement LearningCode1
Reinforcement Learning in an Adaptable Chess Environment for Detecting Human-understandable ConceptsCode1
Curriculum-based Asymmetric Multi-task Reinforcement LearningCode1
Design Process is a Reinforcement Learning ProblemCode1
Residual Skill Policies: Learning an Adaptable Skill-based Action Space for Reinforcement Learning for RoboticsCode1
Show:102550
← PrevPage 18 of 303Next →

Benchmark Results

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