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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 826–850 of 1918 papers

TitleStatusHype
Reinforcement Learning Approach for Multi-Agent Flexible Scheduling Problems—0
Towards Safe Mechanical Ventilation Treatment Using Deep Offline Reinforcement LearningCode0
Interpretable Option Discovery using Deep Q-Learning and Variational Autoencoders—0
Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient—0
Deep Recurrent Q-learning for Energy-constrained Coverage with a Mobile Robot—0
Bayesian Q-learning With Imperfect Expert Demonstrations—0
On Convergence of Average-Reward Off-Policy Control Algorithms in Weakly Communicating MDPs—0
Application of Deep Q Learning with Simulation Results for Elevator Optimization—0
Efficient LSTM Training with Eligibility Traces—0
Predictive Crypto-Asset Automated Market Making Architecture for Decentralized Finance using Deep Reinforcement Learning—0
FIRE: A Failure-Adaptive Reinforcement Learning Framework for Edge Computing Migrations—0
Understanding Hindsight Goal Relabeling from a Divergence Minimization Perspective—0
Comparative Study of Q-Learning and NeuroEvolution of Augmenting Topologies for Self Driving Agents—0
MA2QL: A Minimalist Approach to Fully Decentralized Multi-Agent Reinforcement Learning—0
M^2DQN: A Robust Method for Accelerating Deep Q-learning NetworkCode0
Reinforcement Learning-Based Cooperative P2P Power Trading between DC Nanogrid Clusters with Wind and PV Energy Resources—0
IoT-Aerial Base Station Task Offloading with Risk-Sensitive Reinforcement Learning for Smart Agriculture—0
Deep Reinforcement Learning for Task Offloading in UAV-Aided Smart Farm Networks—0
Structured Q-learning For Antibody Design—0
Route Planning for Last-Mile Deliveries Using Mobile Parcel Lockers: A Hybrid Q-Learning Network ApproachCode0
Reward Delay Attacks on Deep Reinforcement LearningCode0
Q-learning Decision Transformer: Leveraging Dynamic Programming for Conditional Sequence Modelling in Offline RL—0
Double Q-Learning for Citizen Relocation During Natural Hazards—0
On the Convergence of Monte Carlo UCB for Random-Length Episodic MDPs—0
SlateFree: a Model-Free Decomposition for Reinforcement Learning with Slate Actions—0
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