With the robotics book () we're at the end of the chapter, facing the first set of exercises. They are on probability theory and I'm gonna make a photo of the first 2.
Though as a recap, despite notable effort of moderation, going slow and low, and a topic that borders many fields, the participation is extremely low (2 people read the link to the strawpoll at the end of the last thread and voted). It was the same when I tried reading Landau and in the intro to logic. You guys of Veeky Forums, is there any subject or book that could potentially catch on, so that at least 7 or so anons would participate and discuss and do some calculations/coding/tasks? Like at the scale of a 3h/week private investment.
bump ill take a closer look at the exercises this weekend
Owen Watson
In the line of doing it in baby steps, I'm gonna do an intermezzo today and read this chapter "THE BAYESIAN ALGORITHM" (from a known book on Econometrics)
Is Bayes rule a mathematical theorem or more of a principle we want to be true about a theory of probabilities?
Isaac Thompson
its a proven theorem to calculate the probability of x given y so it doesnt give you a definite answer but rather a probability distribution
Thomas Hill
I think you'd be better off looking for people on IRC. On sci you don't get notified for threads or replies or anything and it's not a place people really stick around.
Easton Ward
I've never seen an IRC channel that reasonably sticks to the topic AND has most posts be at least somewhat worth reading. People there aren't keeping their horses before typing random stuff that would make that work.
It's not the format and maybe not even the user base. The situation would just be different if the web were like a class, where people felt any incentive to do some 10+ minutes calculations themselves. A reading group on StackExchange (where people are further down the educational road) would get just as many flakes
Is the Frequentist interpretation of probability theory simply more restrictive than the Bayesian one, or is there more to it?
Sebastian Wilson
no
Jaxson Clark
holy shit this is JUST probability, not your fedora called "probabilistic robotics"
if you literally can't pass a community college first year course in probability (which is what that question is) you need to commit to some sudoku puzzles
Sebastian Garcia
It's the first exercise in a 600 page book, chill and contribute
Christopher Moore
I see that Chapter 1 text, on p.13, asks you to generate random numbers and do basic plotting of regression data.
What are the goto C++ libraries for random number generation, distributions, regression and then plotting? (Also, you may bump with some pigs)
Nathan Robinson
>c++ boost
Dominic Hill
Yes. #include
Lucas Collins
Thx, will use
Yes, I will. You don't seem to get the point og this. It's not about havong the code, and getting results from other anons, but about having done it.
DESU from the stuff I've read in the past, probabilistic robotics/"autonomous agents" etc seem more like a fun way to learn statistics and mess with multi-dimentional data and high-level applied math rather than a useful robotics branch.
You have to hand-type all environment interactions and the control mechanisms, which is really boring and non-generalizeable.
ANN is where it's at tbqh famlad.
Colton Long
Will go into it after the basic graphing stuff, thanks
I was motivated by learning the Kalman filter and the book was recommended. What's ANN?
Artificial Neural Networks? An advisor of me (doing Chemical Kinetics experiements now) did this some 20 years ago and I'm interested in learning more of it. (However, I'm at a quest to pull out some \sci\ participation and for that I'd have to dig into something more basic I think. On the other hamd I could try to go into category theory and clarify some basics to make the threads about it here more accessible)
Cameron Butler
Yeah I was refering to artificial neural networks.
They are resurfacing in all fields, in my uni we also had a few such papers published in the past years by professors. They're about ANN applications in combustion kinetics, predicting reaction species in complex systems etc.
It's a really interesting tool/field but it's out of my reach for now (in terms of available time and mathematical background).
Regarding Veeky Forums participation, you probably shouldn't get your hopes up. Veeky Forums is slow as it is already, the chance of finding people with the appropriate background and enough interest is pretty slim.
If you want real participation you should post here in parallel with some other specialized forum.
Exercise 1: The probability that it is broken given n measurements is:
1/(1+99/3^n)
You get there by setting up a decisiontree and observing that the absolute probability of it being broken is 0.01 and the probability of getting n measurements under 1m is 0.99/3^n.
Normalising gives the above answer. Am I correct?
Ayden Stewart
Yes! I got there schematically using Bayes theorem in pic related, pt. 11.
p_n = 1 / (1 + (1/p_init - 1) * r^n)
That's the same logic. I didn't discuss exercise 2 or any beyond it, and there are several programming tasks open from thw weeks that we cooked up
Robert Thompson
I have not read any of the book but I took a look at your summary page. You wrote "the book does classical mechanics but with probability density functions". Do you mean classical mechanics in the sense of hamiltonians and lagrangians?
Carter Torres
No, I meant that the math feels like as if you do rigid body mechanics, and they keep it on the algorithmic side of it.
In any case, since only 2 people here read along in the book, I think I'll focus more on the programming stuff now - there's more people responding to this sort of thing
Nathan Foster
Pretty sure I'm gonna buy the Stroustroup book (not the translation, thought) Then again, it's pretty thick and feels more like half a reference.
Any criticism or, bettee, alternative recommendation?
