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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 1361–1370 of 1918 papers

TitleStatusHype
Enhanced Rolling Horizon Evolution Algorithm with Opponent Model Learning: Results for the Fighting Game AI Competition—0
Learning medical triage from clinicians using Deep Q-Learning—0
Robust Q-learning—0
A Distributional Analysis of Sampling-Based Reinforcement Learning Algorithms—0
Convergence of Recursive Stochastic Algorithms using Wasserstein Divergence—0
Q-Learning in Regularized Mean-field Games—0
Using Deep Reinforcement Learning Methods for Autonomous Vessels in 2D EnvironmentsCode1
Distributed Reinforcement Learning for Cooperative Multi-Robot Object Manipulation—0
FlapAI Bird: Training an Agent to Play Flappy Bird Using Reinforcement Learning TechniquesCode1
Deep Constrained Q-learning—0
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