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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 1526–1550 of 1918 papers

Title	Date	Tasks	Status	Hype
Learn How to Cook a New Recipe in a New House: Using Map Familiarization, Curriculum Learning, and Bandit Feedback to Learn Families of Text-Based Adventure Games	Aug 13, 2019	Common Sense ReasoningQ-Learning	CodeCode Available	0
Large-Scale Traffic Signal Control Using a Novel Multi-Agent Reinforcement Learning	Aug 10, 2019	Multi-agent Reinforcement LearningQ-Learning	—Unverified	0
Batch Recurrent Q-Learning for Backchannel Generation Towards Engaging Agents	Aug 6, 2019	Imitation LearningQ-Learning	—Unverified	0
Control of nonlinear, complex and black-boxed greenhouse system with reinforcement learning	Jul 30, 2019	Q-Learningreinforcement-learning	CodeCode Available	0
Q-MIND: Defeating Stealthy DoS Attacks in SDN with a Machine-learning based Defense Framework	Jul 27, 2019	Anomaly DetectionBIG-bench Machine Learning	—Unverified	0
Towards Model-based Reinforcement Learning for Industry-near Environments	Jul 27, 2019	Deep Reinforcement LearningModel-based Reinforcement Learning	CodeCode Available	0
Potential-Based Advice for Stochastic Policy Learning	Jul 20, 2019	Q-LearningReinforcement Learning	—Unverified	0
Photonic architecture for reinforcement learning	Jul 17, 2019	Active LearningQ-Learning	—Unverified	0
Model-free Control of Chaos with Continuous Deep Q-learning	Jul 16, 2019	Q-Learningreinforcement-learning	—Unverified	0
An Optimistic Perspective on Offline Reinforcement Learning	Jul 10, 2019	Atari GamesDiversity	CodeCode Available	1
An intelligent financial portfolio trading strategy using deep Q-learning	Jul 8, 2019	Q-Learning	CodeCode Available	0
Q-learning pour la r\'esolution des anaphores pronominales en langue arabe (Q-learning for pronominal anaphora resolution in Arabic texts)	Jul 1, 2019	Q-Learning	—Unverified	0
Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog	Jun 30, 2019	Deep Reinforcement LearningOpen-Domain Dialog	—Unverified	0
QFlip: An Adaptive Reinforcement Learning Strategy for the FlipIt Security Game	Jun 27, 2019	OpenAI GymQ-Learning	CodeCode Available	0
Q-Learning Inspired Self-Tuning for Energy Efficiency in HPC	Jun 26, 2019	Q-Learning	—Unverified	0
Towards Empathic Deep Q-Learning	Jun 26, 2019	EthicsQ-Learning	CodeCode Available	0
Deceptive Reinforcement Learning Under Adversarial Manipulations on Cost Signals	Jun 24, 2019	Q-Learningreinforcement-learning	—Unverified	0
Optimal Use of Experience in First Person Shooter Environments	Jun 24, 2019	Q-LearningReinforcement Learning	—Unverified	0
In Hindsight: A Smooth Reward for Steady Exploration	Jun 24, 2019	Atari GamesQ-Learning	—Unverified	0
Neural networks with motivation	Jun 23, 2019	Hierarchical Reinforcement LearningNavigate	—Unverified	0
Reinforcement Learning-Based Trajectory Design for the Aerial Base Stations	Jun 23, 2019	Q-Learningreinforcement-learning	—Unverified	0
A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatry	Jun 21, 2019	Decision MakingLifelong learning	CodeCode Available	1
Split Q Learning: Reinforcement Learning with Two-Stream Rewards	Jun 21, 2019	Decision MakingQ-Learning	CodeCode Available	1
Cache-Aided NOMA Mobile Edge Computing: A Reinforcement Learning Approach	Jun 20, 2019	Edge-computingQ-Learning	—Unverified	0
Reward Prediction Error as an Exploration Objective in Deep RL	Jun 19, 2019	Atari GamesContinuous Control	—Unverified	0

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