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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 361–370 of 1918 papers

Title	Date	Tasks	Status	Hype	Score
Deep Quality-Value (DQV) Learning	Sep 30, 2018	Atari GamesDeep Reinforcement Learning	CodeCode Available	0	5
Lookahead-Bounded Q-Learning	Jun 28, 2020	Q-Learning	CodeCode Available	0	5
DeepQTest: Testing Autonomous Driving Systems with Reinforcement Learning and Real-world Weather Data	Oct 8, 2023	Autonomous DrivingQ-Learning	CodeCode Available	0	5
M^2DQN: A Robust Method for Accelerating Deep Q-learning Network	Sep 16, 2022	Q-Learningreinforcement-learning	CodeCode Available	0	5
Deep reinforcement learning for time series: playing idealized trading games	Mar 11, 2018	Deep Reinforcement LearningQ-Learning	CodeCode Available	0	5
BAIL: Best-Action Imitation Learning for Batch Deep Reinforcement Learning	Oct 27, 2019	Deep Reinforcement LearningImitation Learning	CodeCode Available	0	5
AlignIQL: Policy Alignment in Implicit Q-Learning through Constrained Optimization	May 28, 2024	D4RLOffline RL	CodeCode Available	0	5
Compressed Federated Reinforcement Learning with a Generative Model	Mar 26, 2024	modelQ-Learning	CodeCode Available	0	5
Deep Q-Learning based Reinforcement Learning Approach for Network Intrusion Detection	Nov 27, 2021	Intrusion DetectionNetwork Intrusion Detection	CodeCode Available	0	5
Deep Q learning for fooling neural networks	Nov 13, 2018	Q-LearningReinforcement Learning	CodeCode Available	0	5

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