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 31263150 of 15113 papers

TitleStatusHype
Crown Jewels Analysis using Reinforcement Learning with Attack Graphs0
Cross-Domain Perceptual Reward Functions0
A Survey of Explainable Reinforcement Learning0
A Survey of Reinforcement Learning-Based Motion Planning for Autonomous Driving: Lessons Learned from a Driving Task Perspective0
CT-DQN: Control-Tutored Deep Reinforcement Learning0
adaPARL: Adaptive Privacy-Aware Reinforcement Learning for Sequential-Decision Making Human-in-the-Loop Systems0
Deep Reinforcement Learning Based Mobile Edge Computing for Intelligent Internet of Things0
Deep Reinforcement Learning based Model-free On-line Dynamic Multi-Microgrid Formation to Enhance Resilience0
CtRL-Sim: Reactive and Controllable Driving Agents with Offline Reinforcement Learning0
Deep Reinforcement Learning Based on Location-Aware Imitation Environment for RIS-Aided mmWave MIMO Systems0
CTSAC: Curriculum-Based Transformer Soft Actor-Critic for Goal-Oriented Robot Exploration0
cube2net: Efficient Query-Specific Network Construction with Data Cube Organization0
CubeTR: Learning to Solve the Rubik's Cube using Transformers0
CubeTR: Learning to Solve The Rubiks Cube Using Transformers0
CUDC: A Curiosity-Driven Unsupervised Data Collection Method with Adaptive Temporal Distances for Offline Reinforcement Learning0
Cumulative Prospect Theory Meets Reinforcement Learning: Prediction and Control0
A Survey of Temporal Credit Assignment in Deep Reinforcement Learning0
Curiosity Based Reinforcement Learning on Robot Manufacturing Cell0
Deep Reinforcement Learning Based Power Allocation for D2D Network0
Curiosity-Driven Experience Prioritization via Density Estimation0
Curiosity-driven Exploration for Mapless Navigation with Deep Reinforcement Learning0
Curiosity-driven Exploration in Sparse-reward Multi-agent Reinforcement Learning0
A Survey on Data-Centric AI: Tabular Learning from Reinforcement Learning and Generative AI Perspective0
Curiosity-Driven Recommendation Strategy for Adaptive Learning via Deep Reinforcement Learning0
CROPS: A Deployable Crop Management System Over All Possible State Availabilities0
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Benchmark Results

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