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 701750 of 15113 papers

TitleStatusHype
Cross-Domain Policy Adaptation by Capturing Representation MismatchCode1
Cross-Embodiment Robot Manipulation Skill Transfer using Latent Space AlignmentCode1
Contextualized Rewriting for Text SummarizationCode1
Context-aware Dynamics Model for Generalization in Model-Based Reinforcement LearningCode1
Ctrl-DNA: Controllable Cell-Type-Specific Regulatory DNA Design via Constrained RLCode1
Affordance Learning from Play for Sample-Efficient Policy LearningCode1
Accelerating Quadratic Optimization with Reinforcement LearningCode1
Curious Hierarchical Actor-Critic Reinforcement LearningCode1
Actor-Attention-Critic for Multi-Agent Reinforcement LearningCode1
CURL: Contrastive Unsupervised Representations for Reinforcement LearningCode1
Curriculum Offline Imitation LearningCode1
Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain AdaptationCode1
Contextualize Me -- The Case for Context in Reinforcement LearningCode1
Distributed Multi-Agent Reinforcement Learning with One-hop Neighbors and Compute Straggler MitigationCode1
Data-Efficient Reinforcement Learning with Self-Predictive RepresentationsCode1
DataLight: Offline Data-Driven Traffic Signal ControlCode1
Contention Window Optimization in IEEE 802.11ax Networks with Deep Reinforcement LearningCode1
Content Masked Loss: Human-Like Brush Stroke Planning in a Reinforcement Learning Painting AgentCode1
Contingency-Aware Influence Maximization: A Reinforcement Learning ApproachCode1
Continuous Coordination As a Realistic Scenario for Lifelong LearningCode1
Decision Transformer: Reinforcement Learning via Sequence ModelingCode1
Decomposed Mutual Information Optimization for Generalized Context in Meta-Reinforcement LearningCode1
Decoupling Strategy and Generation in Negotiation DialoguesCode1
Decoupling Value and Policy for Generalization in Reinforcement LearningCode1
Deep Actor-Critic Learning for Distributed Power Control in Wireless Mobile NetworksCode1
Deep Black-Box Reinforcement Learning with Movement PrimitivesCode1
Accelerating Reinforcement Learning with Learned Skill PriorsCode1
Deep Intrinsically Motivated Exploration in Continuous ControlCode1
Control-Oriented Model-Based Reinforcement Learning with Implicit DifferentiationCode1
Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent SpaceCode1
Actor-Critic Reinforcement Learning for Control with Stability GuaranteeCode1
A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learningCode1
A Game-Theoretic Approach to Multi-Agent Trust Region OptimizationCode1
DeepMind Lab2DCode1
Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions ModelingCode1
Deep Reinforcement Learning based Evasion Generative Adversarial Network for Botnet DetectionCode1
Deep-Reinforcement-Learning-based Path Planning for Industrial Robots using Distance Sensors as ObservationCode1
Deep Reinforcement Learning Control of Quantum CartpolesCode1
Age-Based Scheduling for Mobile Edge Computing: A Deep Reinforcement Learning ApproachCode1
Deep Reinforcement Learning for Active Human Pose EstimationCode1
A General Contextualized Rewriting Framework for Text SummarizationCode1
Comparing Deep Reinforcement Learning Algorithms in Two-Echelon Supply ChainsCode1
CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and SimplicityCode1
Deep Reinforcement Learning for Entity AlignmentCode1
Deep reinforcement learning for large-scale epidemic controlCode1
Deep Reinforcement Learning for List-wise RecommendationsCode1
Accelerating Robot Learning of Contact-Rich Manipulations: A Curriculum Learning StudyCode1
Deep Reinforcement Learning for Process SynthesisCode1
Deep Reinforcement learning for real autonomous mobile robot navigation in indoor environmentsCode1
Accelerating lifelong reinforcement learning via reshaping rewardsCode1
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Benchmark Results

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