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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3626–3650 of 15113 papers

TitleStatusHype
Balancing Act: Prioritization Strategies for LLM-Designed Restless Bandit Rewards—0
Query-Efficient Video Adversarial Attack with Stylized Logo—0
Leveraging Unlabeled Data Sharing through Kernel Function Approximation in Offline Reinforcement LearningCode0
Domain Adaptation for Offline Reinforcement Learning with Limited Samples—0
Using Part-based Representations for Explainable Deep Reinforcement Learning—0
Advances in Preference-based Reinforcement Learning: A Review—0
Offline Model-Based Reinforcement Learning with Anti-Exploration—0
The Evolution of Reinforcement Learning in Quantitative Finance: A Survey—0
Integrating Multi-Modal Input Token Mixer Into Mamba-Based Decision Models: Decision MetaMamba—0
MalLight: Influence-Aware Coordinated Traffic Signal Control for Traffic Signal Malfunctions—0
Efficient Exploration in Deep Reinforcement Learning: A Novel Bayesian Actor-Critic Algorithm—0
World Models Increase Autonomy in Reinforcement Learning—0
Enhancing Reinforcement Learning Through Guided Search—0
Ancestral Reinforcement Learning: Unifying Zeroth-Order Optimization and Genetic Algorithms for Reinforcement Learning—0
Reinforcement learning-based adaptive speed controllers in mixed autonomy condition—0
Vanilla Gradient Descent for Oblique Decision TreesCode0
Model-based RL as a Minimalist Approach to Horizon-Free and Second-Order Bounds—0
Neural Reward MachinesCode0
CAT: Caution Aware Transfer in Reinforcement Learning via Distributional Risk—0
BCR-DRL: Behavior- and Context-aware Reward for Deep Reinforcement Learning in Human-AI Coordination—0
Experimental evaluation of offline reinforcement learning for HVAC control in buildingsCode0
Online Behavior Modification for Expressive User Control of RL-Trained Robots—0
Adaptive User Journeys in Pharma E-Commerce with Reinforcement Learning: Insights from SwipeRx—0
Off-Policy Reinforcement Learning with High Dimensional Reward—0
Large Language Models Prompting With Episodic Memory—0
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Benchmark Results

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