Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

How to implement MAAC/MFAC for Gaussian Squeezing? #11

Open
rezunli96 opened this issue Mar 10, 2019 · 1 comment
Open

How to implement MAAC/MFAC for Gaussian Squeezing? #11

rezunli96 opened this issue Mar 10, 2019 · 1 comment

Comments

@rezunli96
Copy link

rezunli96 commented Mar 10, 2019

Hi I recently get some confusion when trying to reproduce your work, particular about experiment (1) on gaussian squeezing. According to my understanding in order to implement MAA2C algorithm as described in the DeepMind's NeurIPS 17 paper, the critic network should represent the Q-value function which takes joint action of the players into input. However, it seems that gaussian squeeze task is a stateless environment. According to your implementation details, there is a discount factor \gamma for AC methods but not for Q-learning method. So how do you define the state for gaussian squeezing? And if it is stateless, how can one use A2C methods?

@rezunli96 rezunli96 reopened this Mar 14, 2019
@rezunli96 rezunli96 changed the title How to implement MAA2C with so many agents? How to implement MAAC/MFAC for Gaussian Squeezing? Apr 20, 2019
@Amanda2024
Copy link

The same question? How can we get the code for gaussian squeezing?

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants