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It really depends on what you're interested in, its like saying I really want to learn computers.

I'm a Greek and this article saddens me.

Greece is run by a populist government, one of the two parties that had be running Greece to it's demise. Kyriakos Mitsotakis is the first Greek politician in my opinion to understand modern media and how to manipulate them, appearing as the sensible choice to people who don't put any effort into researching politics.

All that while we've had the government donating millions to friendly media,

the Greek version of Watergate, with the goverment spying on politicians, journalists and others

and two trains colliding because of state incompetence with many students dying.

All that have not been investigated properly.

Finally the average greek person has not been feeling any "fastest improving business environments" one of the reasons being that the sectors that thrive are not beneficial to the country.

The best you can do is 0.42, see a subcomment I made below. max force is limited to +-50

There is a mistake in my first comment, the system is described by x'' = -1.00204*x' + u , I forgot a '. Also in the second example , where there is no x' term, you can reach the origin in 0.4 using this strategy.

I just spent too much time messing around with this, so here's the results. The simulation has a limit on the maximum magnitude of the force of your controller, which in this example is 50. The system is described by x'' = -1.00204*x + u (by experimenting with console.log). The theoretical solution to minimize time to the origin on a system like this is a bang-bang strategy: go full actuation and at some point slam the breaks to stop exactly at the origin. Using this strategy you can calculate that you should hit the brakes(-50) starting at x= − 0.867, with the system arriving at the origin at t=0.403. But the timestep of the simulation is dt =0.02, so the system goes from x=-0.874060101875918 to x = -0.6686069466721608 in one timestep, missing the critical switching point. If you try to switch at -0.6686069466721608 it overshoots and at -0.874060101875918 its almost there when t = 0.4 but not good enough for the simulation to decide you finished the challenge. So 0.42 has to be the best you can do. What you controller actually does, due to the actuation limits, is almost the strategy described above, staying either at 50 or -50, except for 3 time points, which make the dynamics just right to land on the origin.

Indeed, the optimal trajectory is to accelerate as hard as possible then decelerate as hard as possible so you land at 0 with dx=0.

It's more exciting to calculate the dynamics if you need to be jerk limited.

It's actually a concern due to simulation error.

The ideal solution, given that there is not input limit, depends on the simulation accuracy. Theoretically, you could achieve 0 time solutions.

Shouldn't this have some thrust limits? I'm not sure if they are added later(I've only seen the first example), but it would make the problems more realistic, interesting and related to control theory.

I believe there are hidden ones.

Yes, after doing some testing with console.log even in the first examples, thrust magnitude is limited to 50.

Hi, first of all congrats for your effort, but I think this is hitting a little bit on the HN information/app hoarder mentality for many commenters and not from people actually planning to use it. I don't think that there is an extreme amount of transfer from learning the fretboard on your website and on the guitar, as there is a different context from using your mouse to select a note on a image representation of the fretboard and on a real guitar. I don't think it wouldn't work, but it would be much better if there was an actual guitar involved, like using the microphone to identify if the user played the correct note on a real guitar.

Hey I personally think there's at least a 90%+ transfer rate. Whether thats extreme or not is left to your judgement. When I navigate the fretboard, a LOT of my navigation is done visually (based on the dot inlays, notes from other strings etc). If you want to know how much of your fretboard navigation is visual, try playing a guitar with no inlays and you can quickly find out.

Playing this game is forcing you to use those immediate visual cues to memorize the notes and that part transfers really well. The bit thats missing is

1) The game's perspective is artifical. Noone looks at their guitar like that. Thankfully our brains our fully capable of maintaining spatial orientation while handling perspective shift. You can stand in the middle of Manhattan , look at google maps and translate a squiggly blue line to a 3 dimensional navigation path that looks nothing like it. Fretboard navigation isnt that much different from Manhattan navigation if you think about it.

2) There's a lot that I know about my guitars from just the sense of touch. 4th string 2nd fret (E) feels very comfortable under my fingers. 3rd string 2nd fret (A) does not. The string cuts into my finger because its still thick but its not coiled. The same string on the 12th fret feels very different because of the tension and the raised action. All that sensory data associated with each note is lost when you use a poor facsimile like a computer game to substitute a real world concept. Which is why I view this as a supplement and not a substitution

Microphones...yeah...more work..more complexity for fewer gains IMHO. I view this as app as great for squeezing guitar time when you're without a guitar: Eating lunch at office desk, commuting by train/bus etc. That part gets lost with the microphone business

Anyways, long rant. Let me know what you think

Sorry that was a long rant.