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

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Showing 3101–3150 of 15113 papers

TitleStatusHype
A Survey of Meta-Reinforcement Learning—0
Overcoming Catastrophic Interference in Online Reinforcement Learning with Dynamic Self-Organizing Maps—0
Deep Reinforcement Learning based Optimal Control of Hot Water Systems—0
Deep Reinforcement Learning Based Power control for Wireless Multicast Systems—0
A Survey of Knowledge-based Sequential Decision Making under Uncertainty—0
A Survey of Inverse Reinforcement Learning: Challenges, Methods and Progress—0
AdaPool: A Diurnal-Adaptive Fleet Management Framework using Model-Free Deep Reinforcement Learning and Change Point Detection—0
A Survey of In-Context Reinforcement Learning—0
A Survey of Imitation Learning: Algorithms, Recent Developments, and Challenges—0
Cross Learning in Deep Q-Networks—0
Crossing the Human-Robot Embodiment Gap with Sim-to-Real RL using One Human Demonstration—0
Deep Reinforcement Learning Based Multi-Access Edge Computing Schedule for Internet of Vehicle—0
Deep Reinforcement Learning Based Networked Control with Network Delays for Signal Temporal Logic Specifications—0
Cross-Embodiment Dexterous Grasping with Reinforcement Learning—0
A Survey of Zero-shot Generalisation in Deep Reinforcement Learning—0
Cross-Domain Transfer via Semantic Skill Imitation—0
Cross-Domain Transfer in Reinforcement Learning using Target Apprentice—0
A Survey of Forex and Stock Price Prediction Using Deep Learning—0
CrossNorm: On Normalization for Off-Policy Reinforcement Learning—0
Cross-State Self-Constraint for Feature Generalization in Deep Reinforcement Learning—0
A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning and ABC—0
Agent with Tangent-based Formulation and Anatomical Perception for Standard Plane Localization in 3D Ultrasound—0
A Survey of Exploration Methods in Reinforcement Learning—0
Crowd-PrefRL: Preference-Based Reward Learning from Crowds—0
Acceleration of Actor-Critic Deep Reinforcement Learning for Visual Grasping in Clutter by State Representation Learning Based on Disentanglement of a Raw Input Image—0
Crown Jewels Analysis using Reinforcement Learning with Attack Graphs—0
Cross-Domain Perceptual Reward Functions—0
A Survey of Explainable Reinforcement Learning—0
A Survey of Reinforcement Learning-Based Motion Planning for Autonomous Driving: Lessons Learned from a Driving Task Perspective—0
CT-DQN: Control-Tutored Deep Reinforcement Learning—0
adaPARL: Adaptive Privacy-Aware Reinforcement Learning for Sequential-Decision Making Human-in-the-Loop Systems—0
Deep Reinforcement Learning Based Mobile Edge Computing for Intelligent Internet of Things—0
Deep Reinforcement Learning based Model-free On-line Dynamic Multi-Microgrid Formation to Enhance Resilience—0
CtRL-Sim: Reactive and Controllable Driving Agents with Offline Reinforcement Learning—0
Deep Reinforcement Learning Based on Location-Aware Imitation Environment for RIS-Aided mmWave MIMO Systems—0
CTSAC: Curriculum-Based Transformer Soft Actor-Critic for Goal-Oriented Robot Exploration—0
cube2net: Efficient Query-Specific Network Construction with Data Cube Organization—0
CubeTR: Learning to Solve the Rubik's Cube using Transformers—0
CubeTR: Learning to Solve The Rubiks Cube Using Transformers—0
CUDC: A Curiosity-Driven Unsupervised Data Collection Method with Adaptive Temporal Distances for Offline Reinforcement Learning—0
Cumulative Prospect Theory Meets Reinforcement Learning: Prediction and Control—0
A Survey of Temporal Credit Assignment in Deep Reinforcement Learning—0
Curiosity Based Reinforcement Learning on Robot Manufacturing Cell—0
Deep Reinforcement Learning Based Power Allocation for D2D Network—0
Curiosity-Driven Experience Prioritization via Density Estimation—0
Curiosity-driven Exploration for Mapless Navigation with Deep Reinforcement Learning—0
Curiosity-driven Exploration in Sparse-reward Multi-agent Reinforcement Learning—0
A Survey on Data-Centric AI: Tabular Learning from Reinforcement Learning and Generative AI Perspective—0
Curiosity-Driven Recommendation Strategy for Adaptive Learning via Deep Reinforcement Learning—0
CROPS: A Deployable Crop Management System Over All Possible State Availabilities—0
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Benchmark Results

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