Actor loss implementation about bicnet HOT 1 OPEN

Hi, Simon.
Sorry for late checking your issue.
This repository is written 2 years ago, so I can't remember everything :(

When I read your issue, I understood that you intended to make the agents hurry up for reaching the landmark. (-1 reward for every step) Now, my reward shaping is hard-fit for this environment, so every reward function shapings are welcomed. If the reward converges under zero when the agents work well, you never mind about this, it's just my old-style implementation.

I think Actor Loss that you mentioned is implemented to actor choose actions that maximizing Q-value (critic).

If there is more stuff to discuss, please contact me anytime.

from bicnet.