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 12151–12200 of 15113 papers

TitleStatusHype
Sample-Efficient Reinforcement Learning of Koopman eNMPC—0
Sample-efficient reinforcement learning using deep Gaussian processes—0
Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation—0
Sample-Efficient Reinforcement Learning via Counterfactual-Based Data Augmentation—0
Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion—0
Sample Efficient Reinforcement Learning with REINFORCE—0
Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost—0
Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty—0
Sample-efficient Safe Learning for Online Nonlinear Control with Control Barrier Functions—0
Sample Efficient Social Navigation Using Inverse Reinforcement Learning—0
Sampling from Energy-based Policies using Diffusion—0
Sampling Strategies for GAN Synthetic Data—0
Sampling Through the Lens of Sequential Decision Making—0
SAM-R1: Leveraging SAM for Reward Feedback in Multimodal Segmentation via Reinforcement Learning—0
SAM-RL: Sensing-Aware Model-Based Reinforcement Learning via Differentiable Physics-Based Simulation and Rendering—0
SAPO-RL: Sequential Actuator Placement Optimization for Fuselage Assembly via Reinforcement Learning—0
SARI: Structured Audio Reasoning via Curriculum-Guided Reinforcement Learning—0
SAT-MARL: Specification Aware Training in Multi-Agent Reinforcement Learning—0
SatNet: A Benchmark for Satellite Scheduling Optimization—0
Saute RL: Almost Surely Safe Reinforcement Learning Using State Augmentation—0
Say What I Want: Towards the Dark Side of Neural Dialogue Models—0
SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation—0
^2-exploration for Reinforcement Learning—0
Scaffolding Reflection in Reinforcement Learning Framework for Confinement Escape Problem—0
Scalable and Incremental Learning of Gaussian Mixture Models—0
Scalable and Sample Efficient Distributed Policy Gradient Algorithms in Multi-Agent Networked Systems—0
Scalable Bayesian Inverse Reinforcement Learning by Auto-Encoding Reward—0
Scalable Centralized Deep Multi-Agent Reinforcement Learning via Policy Gradients—0
Scalable Communication for Multi-Agent Reinforcement Learning via Transformer-Based Email Mechanism—0
Scalable, Decentralized Multi-Agent Reinforcement Learning Methods Inspired by Stigmergy and Ant Colonies—0
Scalable Deep Reinforcement Learning Algorithms for Mean Field Games—0
Scalable Deep Reinforcement Learning for Routing and Spectrum Access in Physical Layer—0
Scalable Deep Reinforcement Learning for Ride-Hailing—0
Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot—0
Scalable Evolution Strategies Pipeline for Solving the Vehicle Routing Problem—0
Scalable Fragment-Based 3D Molecular Design with Reinforcement Learning—0
Scalable Grid-Aware Dynamic Matching using Deep Reinforcement Learning—0
Scalable Joint Learning of Wireless Multiple-Access Policies and their Signaling—0
Scalable Multi-Agent Inverse Reinforcement Learning via Actor-Attention-Critic—0
Scalable Multi-Agent Offline Reinforcement Learning and the Role of Information—0
Scalable Multi-Agent Reinforcement Learning for Networked Systems with Average Reward—0
Scalable multi-agent reinforcement learning for distributed control of residential energy flexibility—0
Scalable Multi-Agent Reinforcement Learning with General Utilities—0
Scalable Multi-agent Reinforcement Learning for Factory-wide Dynamic Scheduling—0
Scalable Multi-Task Imitation Learning with Autonomous Improvement—0
Scalable Online Disease Diagnosis via Multi-Model-Fused Actor-Critic Reinforcement Learning—0
Scalable photonic reinforcement learning by time-division multiplexing of laser chaos—0
Scalable Planning and Learning Framework Development for Swarm-to-Swarm Engagement Problems—0
Scalable Reinforcement-Learning-Based Neural Architecture Search for Cancer Deep Learning Research—0
Scalable Reinforcement Learning-based Neural Architecture Search—0
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Benchmark Results

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