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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 1861–1870 of 1918 papers

TitleStatusHype
Interactive Spoken Content Retrieval by Deep Reinforcement Learning—0
3D Simulation for Robot Arm Control with Deep Q-Learning—0
Episodic Exploration for Deep Deterministic Policies: An Application to StarCraft Micromanagement Tasks—0
Q-Learning with Basic Emotions—0
Multi Exit Configuration of Mesoscopic Pedestrian Simulation—0
BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems—0
Learning to Communicate with Deep Multi-Agent Reinforcement LearningCode0
ViZDoom: A Doom-based AI Research Platform for Visual Reinforcement LearningCode0
Neurohex: A Deep Q-learning Hex Agent—0
Continuous Deep Q-Learning with Model-based AccelerationCode1
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