i know RIGHT

I feel like the evolution of quick oscillations was frankly quite cool and made sense with such a chaotic system

"but, but i did the task sir!" *nope echoes in distance*

I would argue with him that in such a case "well, you made me so are at fault". Unless of course I had be given free will?

😂😂😂😂😂😂

irl it's impossible so you were right

​​​​@@extremechimpoutSo your claim is that all YT videos with robots doing that are fake? Even with triple ones. In real life it does not wobble as much, everything has friction. It's actually easier irl.

@@MrHardzio4Fun I looked there are no such videos

@@extremechimpout I looked there are many of those video, even quadruple.

​@@extremechimpoutLook harder.

That would be very impressive :D

@@PezzzasWork Your videos are always so clean and well put together. I've finished the video now and the final solution you came up with is great. The idea to incrementally ramp up the difficulty was a stroke of genius that felt so obvious after you said it. Great work showing that paper what's possible!

@@CriticalMonkey623 yeah maybe if you could somehow do that irl you'd actually be able to do a double pendulum balance

If single pendulum is like balancing a broomstick on your finger, then double is like balancing a broom stick on top of another broomstick, on top of your finger. Suddenly it does not seem so easy.

@@anonanon6596 nah i could do it

Yeah he immediately solved a problem that even that professional research paper struggled with, and it intuitively makes perfect sense how the learning can transfer over from the simpler problem to the more complex problem. Goes to show that sometimes all you need is to just reframe the problem.

@@research417If you google it, you’ll find that it was a project report from an undergraduate machine learning course… It’s still a cool approach, though.

For real, when I saw the research paper I thought Pezzz was going to show something else because the “professionals” said it was not possible. It’s amazing how it just took a small change to make it work. Great work pezzz

Thank you!

​@@PezzzasWorkcan you make a video doing those?

@@gus2603absolutely support this 🎉, i want to avoid looking at numbers as much as possible.

Is it made using Python?

Everything is made using C++

boyo do i have some news for you "World's first video of 56 transition controls for a triple inverted pendulum : 3-body problem"

@@andrewferguson6901 That video is not using an AI controller, it's a controller calculated from methods found in control theory.

@@andrewferguson6901lmao i found the video and apparently i already started it at some point

Seems like engineers doing that for years kzfaq.info/get/bejne/md9-YKaDs9jGY3k.html this one some years

Woah there buddy thats enough

It's less "doing a move" and more potential energy being converted into kinetic. If the pendulum falls from its highest position it will be moving fast without a correction. Since it is more stable lower down, it will tend to spend more time rapidly spinning below the axis that slowly spinning above it, unless intervened. And finally, the AI, like any control system has a maximum frequency/speed it can manage, above which it breaks down and essentially become random input. So while the AI might be able to take the slow pendulum and balance it up high, if it then falls, it might not have the skill needed to recover. So every failure mode leads to a rapidly spinning "blender".

@@daniel.lupton i know how the doube pendulum works and i also know the situation is either what you said or the AI gaining reward through some loophole in the reward system since its technically over the parameters once every loop (thought this because blenders became less of a problem with each added condition) But i just wanted to make a visual comparison between malfunctions of AI and toddler brains where they start giving seemingly nonsensical inputs to solve their impossible problems (which is your statement anyways)

@@xwxwvyz1 Yeah sorry I didn't mean to imply you didn't understand it. I think I was just looking for an excuse to explain why the blender thing happens.

Thank you very much!

All AI are essentially just function emulators.

@@PezzzasWorkDefinitely a cool video. If you end up doing a follow-up, here are a couple of things I would like to see (as a control theorist): - test with random disturbances that also take place during the swing-up control. You could also think of this as adding a little noise to the inputs of the NN. I think you would have to include this in the training as the swing-up didn’t look like it would tolerate any sort of disturbance. - It would be nice if you gave the audience the ratio between maximum acceleration and gravity used. - I definitely agree that it makes more sense to use acceleration as the control input.

@@PezzzasWorkalso, I think that “article” you mention on NN-based control of a double pendulum is just a project report from an undergraduate ML course. Finally, if you’re unable to make your NN solution robust to disturbances or noise during the swing-up, you could use the ML approach for the “feed-forward” control, basically as a planned trajectory and add conventional control theory on top to stabilize the trajectory w.r.t. noise/disturbances.

we just need a million dyson spheres so the model training doesnt take 100 years

nah dont need a million just the magic number 7

Do you mean balancing a rope? 😂

@@strecher777 no but I will share it when the time is best!

We need to balance the n-pendulum

Thank you very much!

I will try :)

Thank you!

Look up "World's first video of 56 transition controls for a triple inverted pendulum". It's the world's first video of 56 transition controls for a triple inverted pendulum.

@@themoran2 wow

@@themoran2 It can't balance it as long and consistently as this video's double pendulum. Seeing the AI balance it for much longer than 15 seconds would be nice. It's still really impressive though and I was on the edge of my seat seeing a triple pendulum being balanced.

@@Thomas-ko1nf Seeing as how it's a triple pendulum balanced in real life, it's hardly surprising an AI in a simulated environment is more stable. Then again, it's the world's first video of 56 transition controls for a triple inverted pendulum, not the world's first video of a triple pendulum perpetual balancing act.

@@themoran2 That video is not using an AI. It's from a lab researching control theory. They developped their own method based on control theory.