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Q-Learning

The goal of Q-learning is to learn a policy, which tells an agent what action to take under what circumstances.

( Image credit: Playing Atari with Deep Reinforcement Learning )

Papers

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Showing 1076–1100 of 1918 papers

TitleStatusHype
Learning-Based Strategy Design for Robot-Assisted Reminiscence Therapy Based on a Developed Model for People with Dementia—0
Event-Based Communication in Distributed Q-Learning—0
Catastrophic Interference in Reinforcement Learning: A Solution Based on Context Division and Knowledge DistillationCode0
Deep Reinforcement Learning for Dynamic Band Switch in Cellular-Connected UAV—0
DQLEL: Deep Q-Learning for Energy-Optimized LoS/NLoS UWB Node Selection—0
An Independent Study of Reinforcement Learning and Autonomous Driving—0
DQ-GAT: Towards Safe and Efficient Autonomous Driving with Deep Q-Learning and Graph Attention Networks—0
Maximizing Influence with Graph Neural Networks—0
Modified Double DQN: addressing stability—0
An Elementary Proof that Q-learning Converges Almost Surely—0
Offline Decentralized Multi-Agent Reinforcement Learning—0
SABER: Data-Driven Motion Planner for Autonomously Navigating Heterogeneous RobotsCode0
A DQN-based Approach to Finding Precise Evidences for Fact VerificationCode0
Value-Based Reinforcement Learning for Continuous Control Robotic Manipulation in Multi-Task Sparse Reward Settings—0
A Distributed Intelligence Architecture for B5G Network Automation—0
Double Deep Q-learning Based Real-Time Optimization Strategy for Microgrids—0
Integrating Deep Learning and Augmented Reality to Enhance Situational Awareness in Firefighting Environments—0
Constraints Penalized Q-learning for Safe Offline Reinforcement Learning—0
Q-SMASH: Q-Learning-based Self-Adaptation of Human-Centered Internet of Things—0
Transfer Learning in Multi-Agent Reinforcement Learning with Double Q-Networks for Distributed Resource Sharing in V2X Communication—0
A Penalized Shared-parameter Algorithm for Estimating Optimal Dynamic Treatment Regimens—0
Reinforced Hybrid Genetic Algorithm for the Traveling Salesman Problem—0
Computational Benefits of Intermediate Rewards for Goal-Reaching Policy LearningCode0
Ensemble and Auxiliary Tasks for Data-Efficient Deep Reinforcement LearningCode0
The Least Restriction for Offline Reinforcement Learning—0
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