I have always had a question about mlagents: they randomly select actions at the beginning of training. Can we incorporate human intervention into the training process of mlagents to make them train faster? Is there a corresponding method in mlagents? Looking forward to your answer.
This is amazing. I just starting building some trees in behavior designer, but without a TON of code its always going to look super robotic and end up doing the same predictable stuff every time. This looks like quite the solution.
But doesn't ML Agents use Tensorflow anyway, I presume all the use of Tensorboard, inferred a Tensorflow backend. But the stack is pretty much hidden by the ML Agents hyperparamters and config files anyway. As a novice in Deep ML, I started with Keras, and hence now Tensorflow 2.0. But I am seeing a lot of the new Deep RL algorithms examples being developed and explained through PyTorch based networks, with easier control over which sub networks are frozen. I perceive that Academia has some preference for PyTorch.
Very insightful. 👍
I have always had a question about mlagents: they randomly select actions at the beginning of training. Can we incorporate human intervention into the training process of mlagents to make them train faster? Is there a corresponding method in mlagents? Looking forward to your answer.
Really nice stuff! I plan on using ML for a future vid (probably in 2 vids) and have been watching your vids. They're super helpful!
Actually, ML-Agents can be used for imitation learning, and imitation learning is a supervised learning
This is amazing. I just starting building some trees in behavior designer, but without a TON of code its always going to look super robotic and end up doing the same predictable stuff every time. This looks like quite the solution.
how did it work out for you?
@@Rizzmaster9001 I ended the project, but it could have worked. It takes a LOT of training
any alternatives?
Well you reached 10k subs
is it possible to export my ML model into other languages?
Turns out he is a PyTorch Guy, Where is the Tensorflow Squad? (I am Tensorflow!)
But doesn't ML Agents use Tensorflow anyway, I presume all the use of Tensorboard, inferred a Tensorflow backend. But the stack is pretty much hidden by the ML Agents hyperparamters and config files anyway.
As a novice in Deep ML, I started with Keras, and hence now Tensorflow 2.0. But I am seeing a lot of the new Deep RL algorithms examples being developed and explained through PyTorch based networks, with easier control over which sub networks are frozen. I perceive that Academia has some preference for PyTorch.
Thank you so much.. wow!
Don't do it! Use numpy+matplotlib instead!