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

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Showing 651–700 of 15113 papers

TitleStatusHype
Counterfactual Data Augmentation using Locally Factored DynamicsCode1
Correlation-aware Cooperative Multigroup Broadcast 360° Video Delivery Network: A Hierarchical Deep Reinforcement Learning ApproachCode1
Sample Efficient Reinforcement Learning via Large Vision Language Model DistillationCode1
CROP: Conservative Reward for Model-based Offline Policy OptimizationCode1
CORA: Benchmarks, Baselines, and Metrics as a Platform for Continual Reinforcement Learning AgentsCode1
Coordinated Exploration via Intrinsic Rewards for Multi-Agent Reinforcement LearningCode1
Co-Reinforcement Learning for Unified Multimodal Understanding and GenerationCode1
ConvLab-3: A Flexible Dialogue System Toolkit Based on a Unified Data FormatCode1
Controlling the Risk of Conversational Search via Reinforcement LearningCode1
COOL-MC: A Comprehensive Tool for Reinforcement Learning and Model CheckingCode1
CoRL: Environment Creation and Management Focused on System IntegrationCode1
CropGym: a Reinforcement Learning Environment for Crop ManagementCode1
Contrastive State Augmentations for Reinforcement Learning-Based Recommender SystemsCode1
Contrastive Preference Learning: Learning from Human Feedback without RLCode1
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement LearningCode1
Continuous MDP Homomorphisms and Homomorphic Policy GradientCode1
Continuous Coordination As a Realistic Scenario for Lifelong LearningCode1
Continuous-Time Model-Based Reinforcement LearningCode1
Contrastive Variational Reinforcement Learning for Complex ObservationsCode1
Continual Backprop: Stochastic Gradient Descent with Persistent RandomnessCode1
Continual Learning with Gated Incremental Memories for sequential data processingCode1
Contextualize Me -- The Case for Context in Reinforcement LearningCode1
Contextualized Rewriting for Text SummarizationCode1
Contingency-Aware Influence Maximization: A Reinforcement Learning ApproachCode1
Continual Model-Based Reinforcement Learning with HypernetworksCode1
Contention Window Optimization in IEEE 802.11ax Networks with Deep Reinforcement LearningCode1
Constructions in combinatorics via neural networksCode1
Adversarial Search and Tracking with Multiagent Reinforcement Learning in Sparsely Observable EnvironmentCode1
Continual World: A Robotic Benchmark For Continual Reinforcement LearningCode1
Continuous control with deep reinforcement learningCode1
Continuous Deep Q-Learning with Model-based AccelerationCode1
Adversarial Soft Advantage Fitting: Imitation Learning without Policy OptimizationCode1
Contrastive Active InferenceCode1
Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement LearningCode1
Contrastive Reinforcement Learning of Symbolic Reasoning DomainsCode1
Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RLCode1
AWAC: Accelerating Online Reinforcement Learning with Offline DatasetsCode1
Control-Informed Reinforcement Learning for Chemical ProcessesCode1
Control-Oriented Model-Based Reinforcement Learning with Implicit DifferentiationCode1
Converting Biomechanical Models from OpenSim to MuJoCoCode1
Active Reinforcement Learning for Robust Building ControlCode1
Cooperative Multi-Agent Reinforcement Learning with Sequential Credit AssignmentCode1
COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction EstimationCode1
Aerial View Localization with Reinforcement Learning: Towards Emulating Search-and-RescueCode1
Content Masked Loss: Human-Like Brush Stroke Planning in a Reinforcement Learning Painting AgentCode1
Constrained Variational Policy Optimization for Safe Reinforcement LearningCode1
Constraint-Guided Reinforcement Learning: Augmenting the Agent-Environment-InteractionCode1
Context-aware Dynamics Model for Generalization in Model-Based Reinforcement LearningCode1
A fast balance optimization approach for charging enhancement of lithium-ion battery packs through deep reinforcement learningCode1
Continual Reinforcement Learning with Multi-Timescale ReplayCode1
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Benchmark Results

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