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 2876–2900 of 15113 papers

TitleStatusHype
A Two-stage Framework and Reinforcement Learning-based Optimization Algorithms for Complex Scheduling Problems—0
AirCapRL: Autonomous Aerial Human Motion Capture using Deep Reinforcement Learning—0
Adaptive control of a mechatronic system using constrained residual reinforcement learning—0
A Tutorial Introduction to Reinforcement Learning—0
ATTRITION: Attacking Static Hardware Trojan Detection Techniques Using Reinforcement Learning—0
Attribute Controllable Beautiful Caucasian Face Generation by Aesthetics Driven Reinforcement Learning—0
Attractor Selection in Nonlinear Energy Harvesting Using Deep Reinforcement Learning—0
AI Planning: A Primer and Survey (Preliminary Report)—0
A centralized reinforcement learning method for multi-agent job scheduling in Grid—0
Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning—0
ACNMP: Skill Transfer and Task Extrapolation through Learning from Demonstration and Reinforcement Learning via Representation Sharing—0
Attitude Control of Highly Maneuverable Aircraft Using an Improved Q-learning—0
AIGenC: An AI generalisation model via creativity—0
Teaching on a Budget in Multi-Agent Deep Reinforcement Learning—0
DearFSAC: An Approach to Optimizing Unreliable Federated Learning via Deep Reinforcement Learning—0
Attention Routing: track-assignment detailed routing using attention-based reinforcement learning—0
Attention-Privileged Reinforcement Learning—0
AIGB: Generative Auto-bidding via Conditional Diffusion Modeling—0
Attention Privileged Reinforcement Learning for Domain Transfer—0
Attention or memory? Neurointerpretable agents in space and time—0
AI-Driven Resource Allocation in Optical Wireless Communication Systems—0
Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimization—0
Death and Suicide in Universal Artificial Intelligence—0
Attention Graph for Multi-Robot Social Navigation with Deep Reinforcement Learning—0
Attention-driven Robotic Manipulation—0
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Benchmark Results

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