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 1051–1075 of 15113 papers

TitleStatusHype
Contention Window Optimization in IEEE 802.11ax Networks with Deep Reinforcement LearningCode1
Contextualize Me -- The Case for Context in Reinforcement LearningCode1
Continuous control with deep reinforcement learningCode1
Constrained episodic reinforcement learning in concave-convex and knapsack settingsCode1
Constrained Policy Optimization via Bayesian World ModelsCode1
ADLight: A Universal Approach of Traffic Signal Control with Augmented Data Using Reinforcement LearningCode1
Consistency Models as a Rich and Efficient Policy Class for Reinforcement LearningCode1
Consistent Paths Lead to Truth: Self-Rewarding Reinforcement Learning for LLM ReasoningCode1
Constrained Update Projection Approach to Safe Policy OptimizationCode1
Conservative Q-Learning for Offline Reinforcement LearningCode1
Conservative Offline Distributional Reinforcement LearningCode1
Zero-Shot Reinforcement Learning from Low Quality DataCode1
An Experimental Design Perspective on Model-Based Reinforcement LearningCode1
RELIEF: Reinforcement Learning Empowered Graph Feature Prompt TuningCode1
Conservative and Adaptive Penalty for Model-Based Safe Reinforcement LearningCode1
Reliable Conditioning of Behavioral Cloning for Offline Reinforcement LearningCode1
Constrained Variational Policy Optimization for Safe Reinforcement LearningCode1
Continuous Coordination As a Realistic Scenario for Lifelong LearningCode1
A Distributional Perspective on Reinforcement LearningCode1
Accelerated Sim-to-Real Deep Reinforcement Learning: Learning Collision Avoidance from Human PlayerCode1
Conditional Mutual Information for Disentangled Representations in Reinforcement LearningCode1
Action Guidance: Getting the Best of Sparse Rewards and Shaped Rewards for Real-time Strategy GamesCode1
Confidence Estimation Transformer for Long-term Renewable Energy Forecasting in Reinforcement Learning-based Power Grid DispatchingCode1
Compound AI Systems Optimization: A Survey of Methods, Challenges, and Future DirectionsCode1
CompoSuite: A Compositional Reinforcement Learning BenchmarkCode1
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Benchmark Results

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