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I have alternative options for you, if you don't get anywhere with directly changing the python. 1. Setup cron job that copies the data from the...
Thank you for the clarification :)
Based on answers in other threads, you can only use the no-graphics parameter if you are NOT doing ray casting.
var statsRecorder = Academy.Instance.StatsRecorder; statsRecorder.Add("MyMetric", 1.0); :) That's all you need. "MyMetric" will now show up in...
For simple graphs like this, you can use the Tensorboard integration. Your custom metrics will show up in Tensorboard. See:...
You are correct that you don't need to do anything. The observations from the Perception Sensor will be added to your other observations (if you...
By default, for training, it will use CPU. Based on the recommendations in other threads on this subject, you are better off using your CPU for...
Do you mean you need to do something manual in each environment? The way the --num-envs flag is meant to work is the following: 1. Build an...
I suppose you can always use something like 'netcat' to forward traffic from one machine to the other... I assume the connection is tcp based......
Sorry, I don't know the answer to that. Conceptually I think there is no issue here, as long as the latency between client and server is fast...
Something like: https://github.com/Unity-Technologies/ml-agents/blob/master/docs/Training-on-Amazon-Web-Service.md
For your first question, the answer is yes. Pass the --num-envs N flag to mlagents-learn, where N is the number of environments you want to spawn.
It will do it automatically.
For training you are better off using the CPU here, it's faster.
https://www.tensorflow.org/install/gpu has the versions you need to install. The latest ones will not work (or didn't for me a couple of months ago).
You definitely do not need an observation about the mask.
But to answer your question more directly. I you want your action input to be a boolean, you would need to make sure you are using discrete vector...
What is your agent in this case? What is it that you want your agent to learn to do?
The learning rate and entropy will both decrease over time, this is normal.
mlagents-learn --time-scale=1