<p>Could someone clear my doubt on the loss function used in <a href="https://arxiv.org/pdf/1609.05473.pdf" rel="nofollow noreferrer">SeqGAN paper</a> . The paper uses policy gradient method to train the generator which is a recurrent neural network here.</p>
<ol>
<li>Have I interpreted the terms correctly?</li>
<li>What are we summing over? The entire vocabulary of words?</li>
</ol>
<p>Loss function - my interpretation:
<a href="https://i.sstatic.net/4ux3u.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/4ux3u.png" alt="enter image description here" /></a></p>

CC BY-SA 4.0
2020-10-31T15:09:37.123Z
Try to ask a more specific question and simplify the post. In that way, I think you will attract more people and potentially someone that attempts to answer your question. If you have multiple questions, I suggest that you create 1 post for each of the questions (even if they are related) for the simple reason that simplicity/clarity often attracts more people.
nbro
CC BY-SA 4.0
2020-11-06T17:46:19.537Z
@nbro Thanks for the suggestion. I removed the excess questions because my core doubt is what the term under the summation indicates
Mathav Raj
<reinforcement-learning><papers><generative-adversarial-networks><reinforce><seq2seq>
SeqGAN - Policy gradient objective function interpretation
Mathav Raj
# SeqGAN - Policy gradient objective function interpretation

(Asked by: username_0 on 2020-10-18)

Could someone clear my doubt on the loss function used in [SeqGAN paper](https://arxiv.org/pdf/1609.05473.pdf) . The paper uses policy gradient method to train the generator which is a recurrent neural network here.

1. Have I interpreted the terms correctly?
2. What are we summing over? The entire vocabulary of words?

Loss function - my interpretation:
[![enter image description here](https://i.sstatic.net/4ux3u.png)](https://i.sstatic.net/4ux3u.png)

**Tags:** reinforcement-learning, papers, generative-adversarial-networks, reinforce, seq2seq

> **Comments:**
> **username_1**: Try to ask a more specific question and simplify the post. In that way, I think you will attract more people and potentially someone that attempts to answer your question. If you have multiple questions, I suggest that you create 1 post for each of the questions (even if they are related) for the simple reason that simplicity/clarity often attracts more people.  
> **username_0**: @username_1 Thanks for the suggestion. I removed the excess questions because my core doubt is what the term under the summation indicates  

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## 0 answers

