Statements (30)
Predicate | Object |
---|---|
gptkbp:instanceOf |
gptkb:algorithm
reinforcement learning algorithm |
gptkbp:abbreviation |
gptkb:DQN
|
gptkbp:appliesTo |
gptkb:Atari_2600_games
|
gptkbp:citation |
gptkb:Mnih_et_al.,_2015
|
gptkbp:developedBy |
gptkb:DeepMind
|
gptkbp:field |
gptkb:artificial_intelligence
gptkb:machine_learning gptkb:reinforcement_learning deep learning |
https://www.w3.org/2000/01/rdf-schema#label |
Deep Q-Network
|
gptkbp:influenced |
gptkb:Double_DQN
gptkb:Dueling_DQN gptkb:Rainbow_DQN |
gptkbp:input |
image frames
|
gptkbp:introducedIn |
2013
|
gptkbp:language |
gptkb:Python
|
gptkbp:notableFor |
learning to play video games from raw pixels
|
gptkbp:output |
Q-values
|
gptkbp:platform |
gptkb:TensorFlow
gptkb:PyTorch |
gptkbp:publishedIn |
gptkb:Nature
|
gptkbp:solvedBy |
gptkb:Markov_Decision_Process
|
gptkbp:uses |
gptkb:model
gptkb:Q-learning experience replay target network epsilon-greedy policy |
gptkbp:bfsParent |
gptkb:Q-learning
|
gptkbp:bfsLayer |
5
|