|
gptkbp:instanceOf
|
gptkb:algorithm
|
|
gptkbp:application
|
robotics
video game AI
autonomous control
|
|
gptkbp:basedOn
|
gptkb:Q-learning
|
|
gptkbp:citation
|
high
|
|
gptkbp:developedBy
|
gptkb:DeepMind
|
|
gptkbp:field
|
gptkb:reinforcement_learning
|
|
gptkbp:fullName
|
gptkb:Deep_Q-Network
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
DQN
|
|
gptkbp:influenced
|
gptkb:Double_DQN
gptkb:Dueling_DQN
gptkb:Prioritized_Experience_Replay
gptkb:Rainbow_DQN
|
|
gptkbp:input
|
raw pixels
|
|
gptkbp:introducedIn
|
2013
|
|
gptkbp:notableContributor
|
gptkb:Koray_Kavukcuoglu
gptkb:Volodymyr_Mnih
gptkb:David_Silver
|
|
gptkbp:notablePublication
|
gptkb:Playing_Atari_with_Deep_Reinforcement_Learning
|
|
gptkbp:openSource
|
gptkb:TensorFlow
gptkb:PyTorch
|
|
gptkbp:output
|
Q-values
|
|
gptkbp:publishedIn
|
gptkb:Nature
|
|
gptkbp:solvedBy
|
gptkb:Atari_2600_games
|
|
gptkbp:uses
|
deep neural networks
experience replay
target network
|
|
gptkbp:bfsParent
|
gptkb:Deep_Q-Network
gptkb:OpenAI_Baselines
gptkb:Stable_Baselines
|
|
gptkbp:bfsLayer
|
6
|