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 2901–2925 of 15113 papers

TitleStatusHype
Distributional Reinforcement Learning with Online Risk-awareness Adaption—0
Learning Generalizable Agents via Saliency-Guided Features Decorrelation—0
DeepQTest: Testing Autonomous Driving Systems with Reinforcement Learning and Real-world Weather DataCode0
GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning ModelsCode1
Improving Offline-to-Online Reinforcement Learning with Q Conditioned State Entropy Exploration—0
Optimal Sequential Decision-Making in Geosteering: A Reinforcement Learning Approach—0
Reinforced UI Instruction Grounding: Towards a Generic UI Task Automation API—0
Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced DatasetsCode1
Self-Confirming Transformer for Belief-Conditioned Adaptation in Offline Multi-Agent Reinforcement Learning—0
Improving Reinforcement Learning Efficiency with Auxiliary Tasks in Non-Visual Environments: A Comparison—0
Self-Supervised Neuron Segmentation with Multi-Agent Reinforcement LearningCode1
AURO: Reinforcement Learning for Adaptive User Retention Optimization in Recommender Systems—0
Optimal Control of District Cooling Energy Plant with Reinforcement Learning and MPC—0
RTDK-BO: High Dimensional Bayesian Optimization with Reinforced Transformer Deep kernels—0
LESSON: Learning to Integrate Exploration Strategies for Reinforcement Learning via an Option FrameworkCode0
Safe Exploration in Reinforcement Learning: A Generalized Formulation and Algorithms—0
Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning—0
How the level sampling process impacts zero-shot generalisation in deep reinforcement learning—0
Resilient Legged Local Navigation: Learning to Traverse with Compromised Perception End-to-End—0
Discovering General Reinforcement Learning Algorithms with Adversarial Environment DesignCode1
B-Coder: Value-Based Deep Reinforcement Learning for Program Synthesis—0
Proximal Policy Optimization-Based Reinforcement Learning Approach for DC-DC Boost Converter Control: A Comparative Evaluation Against Traditional Control Techniques—0
Reinforcement Learning with Foundation Priors: Let the Embodied Agent Efficiently Learn on Its Own—0
Multi-Agent Reinforcement Learning for Power Grid Topology OptimizationCode0
Searching for High-Value Molecules Using Reinforcement Learning and Transformers—0
Show:102550
← PrevPage 117 of 605Next →

Benchmark Results

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