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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 211–220 of 1918 papers

Title	Date	Tasks	Status	Hype	Score
A Novel Update Mechanism for Q-Networks Based On Extreme Learning Machines	Jun 4, 2020	Q-Learningreinforcement-learning	CodeCode Available	0	5
Finite-Sample Analysis of Nonlinear Stochastic Approximation with Applications in Reinforcement Learning	May 27, 2019	Q-Learningreinforcement-learning	CodeCode Available	0	5
DeepTraffic: Crowdsourced Hyperparameter Tuning of Deep Reinforcement Learning Systems for Multi-Agent Dense Traffic Navigation	Jan 9, 2018	Autonomous DrivingAutonomous Navigation	CodeCode Available	0	5
Imitating from auxiliary imperfect demonstrations via Adversarial Density Weighted Regression	May 28, 2024	Imitation LearningMuJoCo	CodeCode Available	0	5
GAN Q-learning	May 13, 2018	Distributional Reinforcement LearningOpenAI Gym	CodeCode Available	0	5
Generalized Speedy Q-learning	Nov 1, 2019	Q-LearningReinforcement Learning	CodeCode Available	0	5
A Framework for Automated Cellular Network Tuning with Reinforcement Learning	Aug 13, 2018	ManagementQ-Learning	CodeCode Available	0	5
Generating a Graph Colouring Heuristic with Deep Q-Learning and Graph Neural Networks	Apr 8, 2023	Deep Reinforcement LearningGraph Neural Network	CodeCode Available	0	5
Active inference: demystified and compared	Sep 24, 2019	Atari GamesOpenAI Gym	CodeCode Available	0	5
Deep Reinforcement Learning for Vision-Based Robotic Grasping: A Simulated Comparative Evaluation of Off-Policy Methods	Feb 28, 2018	Deep Reinforcement LearningDiversity	CodeCode Available	0	5

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