How can I have several actions for a DQN in the Reinforcement Learning Toolbox?

6 次查看（过去 30 天）
Rusczak
Rusczak 2019-5-6
评论： Huzaifah Shamim 2020-7-9
I'm trying to define the output of a DQN agent with a custom environment, and can't use the actionInfo = rlFiniteSetSpec() correctly.
I'm trying to control 3 actuators that will receive commands 0 and 1.
I always get number of actions = 1.
And the documentation is not clear as it's a new toolbox.
Any suggestions?
  3 个评论
显示 1更早的评论
Rusczak
Rusczak 2020-7-8
Yes,
I followed Emmanouil's suggestion:
actInfo = rlFiniteSetSpec({[0; 0; 0]; [1; 1; 1]; ...
[1; 0; 0]; [0; 1; 0]; [0; 0; 1]; ...
[1; 1; 0]; [0; 1; 1]; [1; 0; 1]})
Huzaifah Shamim
Huzaifah Shamim 2020-7-9
Oh nice okok. What custom environment where you trying to make?
Also how should I approach it if i have 3 agents (like your three actuators) but 12 actions could be applied to them?

请先登录，再进行评论。

请先登录，再回答此问题。

采纳的回答

Emmanouil Tzorakoleftherakis
If you type
help rlFiniteSetSpec
the second example is
spec = rlFiniteSetSpec({[0,1];[1,1];[1,2];[1,3]})
If you define all possible combinations of the discrete inputs in a cell array as above, that should work (think of a single action as one possible combination of your 3 actuator commands).
I hope this helps.

更多回答（0 个）

类别

在 Help Center 和 File Exchange 中查找有关 Reinforcement Learning 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by