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

Showing 57015750 of 15113 papers

TitleStatusHype
Interpretable Stochastic Model Predictive Control using Distributional Reinforced Estimation for Quadrotor Tracking Systems0
Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments0
Unified Distributed EnvironmentCode0
Efficient Off-Policy Reinforcement Learning via Brain-Inspired Computing0
Deep Reinforcement Learning in mmW-NOMA: Joint Power Allocation and Hybrid Beamforming0
Deep Reinforcement Learning for Computational Fluid Dynamics on HPC SystemsCode1
Distributed Transmission Control for Wireless Networks using Multi-Agent Reinforcement LearningCode0
Joint Power Allocation and Beamformer for mmW-NOMA Downlink Systems by Deep Reinforcement Learning0
Emergent Bartering Behaviour in Multi-Agent Reinforcement Learning0
Towards Understanding the Link Between Modularity and Performance in Neural Networks for Reinforcement LearningCode0
Upside-Down Reinforcement Learning Can Diverge in Stochastic Environments With Episodic ResetsCode0
Provably Safe Reinforcement Learning: Conceptual Analysis, Survey, and Benchmarking0
Feature and Instance Joint Selection: A Reinforcement Learning Perspective0
Provably Safe Deep Reinforcement Learning for Robotic Manipulation in Human Environments0
Contingency-constrained economic dispatch with safe reinforcement learning0
Economical Precise Manipulation and Auto Eye-Hand Coordination with Binocular Visual Reinforcement Learning0
Accounting for the Sequential Nature of States to Learn Features for Reinforcement Learning0
Controlling chaotic itinerancy in laser dynamics for reinforcement learning0
Bridging Model-based Safety and Model-free Reinforcement Learning through System Identification of Low Dimensional Linear Models0
Delayed Reinforcement Learning by Imitation0
Intelligent Reflecting Surface Configurations for Smart Radio Using Deep Reinforcement LearningCode1
Efficient Distributed Framework for Collaborative Multi-Agent Reinforcement Learning0
Final Iteration Convergence Bound of Q-Learning: Switching System Approach0
A State-Distribution Matching Approach to Non-Episodic Reinforcement LearningCode0
Learning to Guide Multiple Heterogeneous Actors from a Single Human Demonstration via Automatic Curriculum Learning in StarCraft II0
Characterizing the Action-Generalization Gap in Deep Q-Learning0
Developing cooperative policies for multi-stage reinforcement learning tasks0
VesNet-RL: Simulation-based Reinforcement Learning for Real-World US Probe NavigationCode1
State Encoders in Reinforcement Learning for Recommendation: A Reproducibility StudyCode1
On the Verge of Solving Rocket League using Deep Reinforcement Learning and Sim-to-sim Transfer0
Hybrid Reinforcement Learning for STAR-RISs: A Coupled Phase-Shift Model Based Beamformer0
Efficient Risk-Averse Reinforcement LearningCode1
Gamma and Vega Hedging Using Deep Distributional Reinforcement LearningCode1
Accelerated Reinforcement Learning for Temporal Logic Control Objectives0
DxFormer: A Decoupled Automatic Diagnostic System Based on Decoder-Encoder Transformer with Dense Symptom RepresentationsCode1
Learning to Brachiate via Simplified Model ImitationCode1
Introduction to Soar0
Simultaneous Double Q-learning with Conservative Advantage Learning for Actor-Critic MethodsCode0
Applications of Reinforcement Learning in Deregulated Power Market: A Comprehensive Review0
Deep Reinforcement Learning-Based Adaptive IRS Control with Limited Feedback Codebooks0
Search-Based Testing of Reinforcement Learning0
JUNO: Jump-Start Reinforcement Learning-based Node Selection for UWB Indoor Localization0
Dynamically writing coupled memories using a reinforcement learning agent, meeting physical bounds0
A Deep Reinforcement Learning-based Sliding Mode Control Design for Partially-known Nonlinear Systems0
Reinforcement Learning Approach to Estimation in Linear Systems0
Goal-Oriented Next Best Activity Recommendation using Reinforcement Learning0
Alternating Good-for-MDP Automata0
How to Spend Your Robot Time: Bridging Kickstarting and Offline Reinforcement Learning for Vision-based Robotic Manipulation0
Generative methods for sampling transition paths in molecular dynamics0
LDSA: Learning Dynamic Subtask Assignment in Cooperative Multi-Agent Reinforcement Learning0
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Benchmark Results

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