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 876–900 of 15113 papers

TitleStatusHype
Constrained Variational Policy Optimization for Safe Reinforcement LearningCode1
Expression might be enough: representing pressure and demand for reinforcement learning based traffic signal controlCode1
Constrained Update Projection Approach to Safe Policy OptimizationCode1
Constraint-Guided Reinforcement Learning: Augmenting the Agent-Environment-InteractionCode1
Constrained episodic reinforcement learning in concave-convex and knapsack settingsCode1
Fault-Tolerant Federated Reinforcement Learning with Theoretical GuaranteeCode1
Feasibility Consistent Representation Learning for Safe Reinforcement LearningCode1
Constrained Policy Optimization via Bayesian World ModelsCode1
Constructions in combinatorics via neural networksCode1
Federated Reinforcement Learning with Environment HeterogeneityCode1
Aligning Language Models with Human Preferences via a Bayesian ApproachCode1
Reliable Conditioning of Behavioral Cloning for Offline Reinforcement LearningCode1
Zero-Shot Reinforcement Learning from Low Quality DataCode1
Finding Effective Security Strategies through Reinforcement Learning and Self-PlayCode1
Alleviating Matthew Effect of Offline Reinforcement Learning in Interactive RecommendationCode1
Consistency Models as a Rich and Efficient Policy Class for Reinforcement LearningCode1
Conservative Offline Distributional Reinforcement LearningCode1
Conservative Q-Learning for Offline Reinforcement LearningCode1
Fine-tuning LLMs for Autonomous Spacecraft Control: A Case Study Using Kerbal Space ProgramCode1
Consistent Paths Lead to Truth: Self-Rewarding Reinforcement Learning for LLM ReasoningCode1
Contention Window Optimization in IEEE 802.11ax Networks with Deep Reinforcement LearningCode1
Adversarial Deep Reinforcement Learning in Portfolio ManagementCode1
Flexible Robust Beamforming for Multibeam Satellite Downlink using Reinforcement LearningCode1
Adversarial Deep Reinforcement Learning for Improving the Robustness of Multi-agent Autonomous Driving PoliciesCode1
Connecting Deep-Reinforcement-Learning-based Obstacle Avoidance with Conventional Global Planners using Waypoint GeneratorsCode1
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Benchmark Results

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