Unity ML-Agents - Watch this first! (Is this framework for you?)

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Before learning Unity ML-Agents, you should watch this to make sure it is the framework for you.
Watch this after: • Unity ML-Agents 1.0 - ...
And then this: • ML-Agents 1.0+ | Creat...
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11 ноя 2020

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Комментарии : 12

@GamingJadenWilliams 16 дней назад

Very insightful. 👍

@TylerGreen 3 года назад

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!

@neuro_corgi 2 года назад

Actually, ML-Agents can be used for imitation learning, and imitation learning is a supervised learning

@munyunu 2 года назад

Thank you so much.. wow!

@ProjectWander 3 года назад

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.

@frediwalker2381 Месяц назад

how did it work out for you?

@ProjectWander 6 дней назад

@@frediwalker2381 I ended the project, but it could have worked. It takes a LOT of training

@keyhaven8151 Месяц назад

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.

@choco2482 Год назад

is it possible to export my ML model into other languages?

@anonymosranger4759 3 года назад

Turns out he is a PyTorch Guy, Where is the Tensorflow Squad? (I am Tensorflow!)

@juleswombat5309 2 года назад

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.