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 5201–5250 of 15113 papers

TitleStatusHype
Hindsight Learning for MDPs with Exogenous InputsCode0
Brick Tic-Tac-Toe: Exploring the Generalizability of AlphaZero to Novel Test EnvironmentsCode0
GriddlyJS: A Web IDE for Reinforcement Learning—0
Continual Meta-Reinforcement Learning for UAV-Aided Vehicular Wireless Networks—0
Towards Global Optimality in Cooperative MARL with the Transformation And Distillation Framework—0
Optimistic PAC Reinforcement Learning: the Instance-Dependent View—0
Learning Bellman Complete Representations for Offline Policy EvaluationCode0
DGPO: Discovering Multiple Strategies with Diversity-Guided Policy OptimizationCode1
Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement LearningCode1
Online Game Level Generation from MusicCode0
Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement LearningCode1
PAC Reinforcement Learning for Predictive State Representations—0
Grounding Aleatoric Uncertainty for Unsupervised Environment Design—0
Don't Start From Scratch: Leveraging Prior Data to Automate Robotic Reinforcement Learning—0
Learning Temporally Extended Skills in Continuous Domains as Symbolic Actions for Planning—0
Reinforcement Learningx2013Based Transient Response Shaping for Microgrids—0
State Dropout-Based Curriculum Reinforcement Learning for Self-Driving at Unsignalized Intersections—0
Deep Reinforcement Learning for Long-Term Voltage Stability Control—0
Ablation Study of How Run Time Assurance Impacts the Training and Performance of Reinforcement Learning Agents—0
High Performance Simulation for Scalable Multi-Agent Reinforcement Learning—0
Interaction Pattern Disentangling for Multi-Agent Reinforcement LearningCode1
CompoSuite: A Compositional Reinforcement Learning BenchmarkCode1
Storehouse: a Reinforcement Learning Environment for Optimizing Warehouse ManagementCode1
Safe reinforcement learning for multi-energy management systems with known constraint functions—0
Reinforced Lin-Kernighan-Helsgaun Algorithms for the Traveling Salesman ProblemsCode1
Variational multiscale reinforcement learning for discovering reduced order closure models of nonlinear spatiotemporal transport systems—0
Domain Adapting Deep Reinforcement Learning for Real-world Speech Emotion Recognition—0
gym-DSSAT: a crop model turned into a Reinforcement Learning environment—0
Evaluating Human-like Explanations for Robot Actions in Reinforcement Learning Scenarios—0
DRL-ISP: Multi-Objective Camera ISP with Deep Reinforcement Learning—0
Stochastic optimal well control in subsurface reservoirs using reinforcement learningCode0
Robust optimal well control using an adaptive multi-grid reinforcement learning frameworkCode0
Vessel-following model for inland waterways based on deep reinforcement learning—0
Multi-objective Optimization of Notifications Using Offline Reinforcement Learning—0
Reinforcement Learning for Distributed Transient Frequency Control with Stability and Safety Guarantees—0
Inferring and Conveying Intentionality: Beyond Numerical Rewards to Logical Intentions—0
Instance-Dependent Near-Optimal Policy Identification in Linear MDPs via Online Experiment Design—0
A Learning System for Motion Planning of Free-Float Dual-Arm Space Manipulator towards Non-Cooperative ObjectCode1
Model Selection in Reinforcement Learning with General Function Approximations—0
Reinforcement Learning Portfolio Manager Framework with Monte Carlo Simulation—0
Deep Reinforcement Learning Approach for Trading Automation in The Stock Market—0
Decentralized scheduling through an adaptive, trading-based multi-agent system—0
AVDDPG: Federated reinforcement learning applied to autonomous platoon control—0
Learning Task Embeddings for Teamwork Adaptation in Multi-Agent Reinforcement LearningCode1
Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICsCode1
CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement LearningCode2
Explainability in Deep Reinforcement Learning, a Review into Current Methods and Applications—0
Robust Reinforcement Learning in Continuous Control Tasks with Uncertainty Set RegularizationCode0
Tackling Real-World Autonomous Driving using Deep Reinforcement Learning—0
Resource Allocation in Multicore Elastic Optical Networks: A Deep Reinforcement Learning Approach—0
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Benchmark Results

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