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 4501–4525 of 15113 papers

TitleStatusHype
From Images to Connections: Can DQN with GNNs learn the Strategic Game of Hex?Code0
Probabilistic Inference in Reinforcement Learning Done Right—0
Risk-sensitive Markov Decision Process and Learning under General Utility Functions—0
Resilient Control of Networked Microgrids using Vertical Federated Reinforcement Learning: Designs and Real-Time Test-Bed Validations—0
Analyzing Behaviors of Mixed Traffic via Reinforcement Learning at Unsignalized Intersections—0
Clustered Policy Decision Ranking—0
Reinforcement Learning and Deep Stochastic Optimal Control for Final Quadratic Hedging—0
Provably Efficient CVaR RL in Low-rank MDPs—0
Offline Reinforcement Learning for Wireless Network Optimization with Mixture Datasets—0
Tactile Active Inference Reinforcement Learning for Efficient Robotic Manipulation Skill Acquisition—0
Benchmarking Feature Extractors for Reinforcement Learning-Based Semiconductor Defect Localization—0
Imagination-Augmented Hierarchical Reinforcement Learning for Safe and Interactive Autonomous Driving in Urban Environments—0
Data-Driven LQR using Reinforcement Learning and Quadratic Neural Networks—0
Runtime Verification of Learning Properties for Reinforcement Learning Algorithms—0
When Mining Electric Locomotives Meet Reinforcement Learning—0
Purpose in the Machine: Do Traffic Simulators Produce Distributionally Equivalent Outcomes for Reinforcement Learning Applications?—0
On-Policy Policy Gradient Reinforcement Learning Without On-Policy Sampling—0
Workflow-Guided Response Generation for Task-Oriented Dialogue—0
Adversarial Imitation Learning On Aggregated Data—0
An introduction to reinforcement learning for neuroscience—0
Investigating Robustness in Cyber-Physical Systems: Specification-Centric Analysis in the face of System Deviations—0
Reinforcement Learning for Solving Stochastic Vehicle Routing ProblemCode0
An advantage based policy transfer algorithm for reinforcement learning with measures of transferability—0
Learning Predictive Safety Filter via Decomposition of Robust Invariant Set—0
Clipped-Objective Policy Gradients for Pessimistic Policy OptimizationCode0
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Benchmark Results

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