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 1001–1050 of 15113 papers

TitleStatusHype
Contingency-Aware Influence Maximization: A Reinforcement Learning ApproachCode1
Contextualize Me -- The Case for Context in Reinforcement LearningCode1
Continual Backprop: Stochastic Gradient Descent with Persistent RandomnessCode1
A Policy-Guided Imitation Approach for Offline Reinforcement LearningCode1
Kalman meets Bellman: Improving Policy Evaluation through Value TrackingCode1
Karolos: An Open-Source Reinforcement Learning Framework for Robot-Task EnvironmentsCode1
Analysis of diversity-accuracy tradeoff in image captioningCode1
A Boolean Task Algebra for Reinforcement LearningCode1
Knowledge-guided Open Attribute Value Extraction with Reinforcement LearningCode1
Leveraging Queue Length and Attention Mechanisms for Enhanced Traffic Signal Control OptimizationCode1
Context-aware Dynamics Model for Generalization in Model-Based Reinforcement LearningCode1
KuaiSim: A Comprehensive Simulator for Recommender SystemsCode1
Language Control Diffusion: Efficiently Scaling through Space, Time, and TasksCode1
LaND: Learning to Navigate from DisengagementsCode1
Accelerating Deep Reinforcement Learning for Digital Twin Network Optimization with Evolutionary StrategiesCode1
Language-Conditioned Reinforcement Learning to Solve Misunderstandings with Action CorrectionsCode1
Adaptive Transformers in RLCode1
Analytical Lyapunov Function Discovery: An RL-based Generative ApproachCode1
Language Reward Modulation for Pretraining Reinforcement LearningCode1
Large Batch Experience ReplayCode1
Contextualized Rewriting for Text SummarizationCode1
Large Language Model as a Policy Teacher for Training Reinforcement Learning AgentsCode1
Continual Learning with Gated Incremental Memories for sequential data processingCode1
Continuous Deep Q-Learning with Model-based AccelerationCode1
Constraint-Guided Reinforcement Learning: Augmenting the Agent-Environment-InteractionCode1
Advancing Multimodal Reasoning via Reinforcement Learning with Cold StartCode1
Constructions in combinatorics via neural networksCode1
Constrained Update Projection Approach to Safe Policy OptimizationCode1
Constrained Variational Policy Optimization for Safe Reinforcement LearningCode1
Contention Window Optimization in IEEE 802.11ax Networks with Deep Reinforcement LearningCode1
Consistent Paths Lead to Truth: Self-Rewarding Reinforcement Learning for LLM ReasoningCode1
Constrained episodic reinforcement learning in concave-convex and knapsack settingsCode1
Reliable Conditioning of Behavioral Cloning for Offline Reinforcement LearningCode1
Zero-Shot Reinforcement Learning from Low Quality DataCode1
Consistency Models as a Rich and Efficient Policy Class for Reinforcement LearningCode1
Constrained Policy Optimization via Bayesian World ModelsCode1
Content Masked Loss: Human-Like Brush Stroke Planning in a Reinforcement Learning Painting AgentCode1
Continuous MDP Homomorphisms and Homomorphic Policy GradientCode1
Connecting Deep-Reinforcement-Learning-based Obstacle Avoidance with Conventional Global Planners using Waypoint GeneratorsCode1
Action Space Shaping in Deep Reinforcement LearningCode1
ConfuciuX: Autonomous Hardware Resource Assignment for DNN Accelerators using Reinforcement LearningCode1
Conservative and Adaptive Penalty for Model-Based Safe Reinforcement LearningCode1
Concise Reasoning via Reinforcement LearningCode1
Computational Performance of Deep Reinforcement Learning to find Nash EquilibriaCode1
Conditional Mutual Information for Disentangled Representations in Reinforcement LearningCode1
CompoSuite: A Compositional Reinforcement Learning BenchmarkCode1
Compositional Reinforcement Learning from Logical SpecificationsCode1
Compound AI Systems Optimization: A Survey of Methods, Challenges, and Future DirectionsCode1
Confidence Estimation Transformer for Long-term Renewable Energy Forecasting in Reinforcement Learning-based Power Grid DispatchingCode1
Conservative Offline Distributional Reinforcement LearningCode1
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Benchmark Results

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