Reinforcement Learning with Stable Baselines 3 - Introduction (P.1)

looking forward for the next episodes. BTW, at the end you were still using random actions after training the model.

Looking forward to the next one!

💥💥💥

❤️ for ❤️

Thank you for this tutorial. I am just getting into AI. It is over my head immediately, but your overview of the parts such as observation and agent were helpful for the bigger picture.

Have you considered unity+mlagents? Why not to go that way?

LETS GOOOOOO THIS IS EXACTLY WHAT I WANTED THANK YOU SO MUCH

How often will these videos be released?? Im so excited to start watching and keep watching tzhe series!!

This is very useful. I'm working on an RL video series myself (the theory side, so no overlap here) and I was just looking for prebuilt RL algos. Stable baseline's 3 is by far the most complete/well tested suite I've come across. This really makes a big differences - thanks!

Also, it's nice to see super technical coverage like can yield a 1M+ followers. Awesome.

Thank you, these video tutorial will be of big help to my thesis. I going to support you.
I have many doubts I hope this can resolved them.

Please add more videos about reinforcement learning

Then can u say how can I make gym to play valorant game 😅 can we do this with gym or can it play call of duty: cold war

Thanks for introducing the Stable Baseline 3,
and yeah sometime we forget to use model!

Does anybody know how to train the model using GPU? I tried changing the model parameter to device='cude', but it's still using cpu device when learning.

You are still taking random actions.

Little heads up for the next video if you can explore it : the saving and loading of a sb3 baseline model depends on the " deterministic " flag.. Sometimes when used the eval procedure given in sb3, even if the u saved the model in deterministic manner you get unstable results. Can you explore that too ? Thank g8 video

What does one use this for IRL?

Don't you have to define a neural model? I mean, what if you have an image as an input? Does Stable Baselines automagically asumes the neural network to pass through de values of the observations?

Awesome

Happy New Year SEndex, was learning machine learning during the lockdown & I had no idea in the Field . U teach so well

Honestly loving this series, i hope you make a indepth tutorial series on this. Thanks

Am I the only one trying to clean the screen from dust looking like a fool at the term explanations? Anyways, great video Harrison, really enjoy your videos!

Very excited for this series. I'm following along and when the lunar lander game displays, it plays incredibly quickly. Probably 4-5 times faster than in the video. Does anyone know how to adjust the speed at which the game plays?

Awesome. Can’t wait for the next one

youre such a beauty man

Great series as always...needs the next step, developing asynchronous (multiprocessing) models, eg: PPO into Asynchronous-PPO (APPO) on custom environments...Thx

I see that yours is using cuda device, how do i make mine use cuda device instead of cpu?

If you're following along using a Conda environment and the Lunar Lander environment gives you an error (namely "module 'gym.envs.box2d' has no attribute 'LunarLander'") then I found that you need to also install two other packages; swig and box2d-py:

conda install -c conda-forge swig box2d-py

Could this algorithm also be used for multi-agent multi-objective environments?

I have watched a bunch of videos about what reinforcement learning can do. But I gave up on the Steve Brunton series. Perhaps I watch this series instead and understand how learning is done everything I did so far has been just gradient based learning. And I don't know if reinforcement learning applies to language. Maybe in a conversational setting.

I have a game from my childhood: Mirror's Edge mobile edition. Which you can't no longer buy as EA removed it from the store instead of updating it. As it essentially just has 6 discrete inputs I could see how it can be learned. But the levels are limited, so it might overfit easily. And rewards can't just be time, as that requires success in the first place.

Hey Sentdex, Actually in env.step() method you have passed the env.action_space.sample() instead of model.predict() !!!!! @sentdex

SentDex youre a legend, brother. The thought of implementing these using deep learning libraries alone, instant grey hair! Thank you

awesome video, learned a lot, keep up the good work

What operating system do you use to run these on?

coding along it doesnt work. at least not in google colab

I followed all the instructions but when I try to run the notebook I get error on the step function; It advise me: raise NotImplememtedError.....>.<.What should I so?

Guys anyone having problem with installing/running stabe baseline in MacBook? I can't run on either MacBook or linux

What does the variable episodes represent here?

I have a small question: why A2C only uses one "MlpPolicy" in Stable_baselines3? Actually, it has two networks, am I right? Thanks.

Im at the start of the tutorial after adding the env.render().. why is it that its not rendering anything when I run the code? I'm running python=3.9 on a windows machine w/ conda

RL in a nutshell. IT NEVER WORKS.

It's really the part of deep learning where you implement a paper and get zero result.

"Your environment must inherit from the gymnasium.Env class cf." can you address this error?

can SB3 be extended to pettingzoo and used for MARL?

I am getting ValueError: too many values to unpack (expected 2) when executing model.learn(), some other people enconountered the same issue but I haven't found a solution.

Can you please talk about how we use the RL to model and optimize satellite networks and HAP( high altitude platforms)??

Can you please talk about how we use the RL to model and optimize satellite networks and HAP( high altitude platforms)??
How we control the direction and angle of a projector embedded into HAP or UAV so that it directs its light beams towards an special area of interest on the Earth??

This guy never misses, best tutorials in the game.

Keeping the env's sample action and your humor made my day :)