Body: <p>Suppose we have a DDPG algorithm.
  The actor has N input nodes, two hidden layers with J nodes, and S output nodes.
  The critic has N+S input nodes, two hidden layers with C nodes, and one output node.
  How does the time complexity of this algorithm could be calculated??</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-11-24T10:53:18.780Z
Comments.Text: Hello. Welcome to Artificial Intelligence Stack Exchange. My question to you is: what have you tried so far to answer your own question? Do you know what the time complexity is?
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-11-24T14:01:05.427Z
Comments.Text: Thanks. yes, I know what it is, and I've found some ways to calculate the neural network's time complexity. But, I wonder is there a difference between neural network complexity and Rl algorithms? also in a paper related to my work there was a Q-learning time complexity analysis. But I couldn't find anything for actor-critic methods like DDPG.
Comments.UserDisplayName: farnad
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-11-24T14:05:37.897Z
Comments.Text: I would recommend that you first provide the pseudocode of the algorithm (and the link to the paper that contains the algorithm/pseudocode) that you referring to, so that to make sure we're talking about the same thing.
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-11-24T14:10:47.250Z
Comments.Text: I thought my question was clear enough. It's the DDPG paper [link](https://arxiv.org/abs/1509.02971). and I've found this very helpful for neural networks [link] (https://ai.stackexchange.com/questions/5728/what-is-the-time-complexity-for-training-a-neural-network-using-back-propagation)
Comments.UserDisplayName: farnad
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-11-24T15:06:03.880Z
Comments.Text: So, which algorithm in that paper are you talking about? Algorithm 1? As I said above, please, edit your post to directly include these details there.
Comments.UserDisplayName: nbro
Tags: <neural-networks><reinforcement-learning><time-complexity>
Title: What is the time complexity of DDPG algorithm?
UserDisplayName: farnad
ThreadText: # What is the time complexity of DDPG algorithm?
  
  (Asked by: username_0 on 2021-11-24)
  
  Suppose we have a DDPG algorithm.
  The actor has N input nodes, two hidden layers with J nodes, and S output nodes.
  The critic has N+S input nodes, two hidden layers with C nodes, and one output node.
  How does the time complexity of this algorithm could be calculated??
  
  **Tags:** neural-networks, reinforcement-learning, time-complexity
  > **Comments:**
  > **username_1**: Hello. Welcome to Artificial Intelligence Stack Exchange. My question to you is: what have you tried so far to answer your own question? Do you know what the time complexity is?  
  > **username_0**: Thanks. yes, I know what it is, and I've found some ways to calculate the neural network's time complexity. But, I wonder is there a difference between neural network complexity and Rl algorithms? also in a paper related to my work there was a Q-learning time complexity analysis. But I couldn't find anything for actor-critic methods like DDPG.  
  > **username_1**: I would recommend that you first provide the pseudocode of the algorithm (and the link to the paper that contains the algorithm/pseudocode) that you referring to, so that to make sure we're talking about the same thing.  
  > **username_0**: I thought my question was clear enough. It's the DDPG paper [link](https://arxiv.org/abs/1509.02971). and I've found this very helpful for neural networks [link] (https://ai.stackexchange.com/questions/5728/what-is-the-time-complexity-for-training-a-neural-network-using-back-propagation)  
  > **username_1**: So, which algorithm in that paper are you talking about? Algorithm 1? As I said above, please, edit your post to directly include these details there.  
  
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  ## 0 answers
  
  