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Prof. Sussman's Reading List

437 points| jonnybgood | 11 years ago |aurellem.org | reply

75 comments

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[+] kjak|11 years ago|reply
I'm happy to see The Variational Principles of Mechanics (by the great Lanczos) on that list. It really is deep, and I think it does a fantastic job of explaining classical mechanics. I've read the vast majority of the book multiple times.

Since we're on the topic of Sussman, has anyone here read through SICM? I've heard that the code is difficult to get to work, but does anyone have an opinion on the rest? I haven't had a chance to read it yet.

Anyone read both Lanczos and SICM?

[+] tjl|11 years ago|reply
I referred to the Lanczos book quite often when I was working on my PhD. I've read the first part of SICM and skimmed the rest. Based on that, it looks like it does an excellent job in building up an understanding of how the math works. By the time I looked at SICM, I had implemented my own code to do something similar (coded in Maple). It looked like the progression of the code was well handled. On the whole, I think Lanczos is a better book, but SICM is fairly decent. I'm also partial to Meirovitch's Methods of Analytical Dynamics which I think does the best job of explaining the inclusion of non-conservative forces in the Principle of Least Action. This is needed for applied forces and torques like a motor. It also covers the inclusion of damping forces well. Like Lanczos, the Meirovitch book is available from Dover, so it's pretty inexpensive.

The SICM code really only works for a specific scheme interpreter, so if you have that it should be fine.

[+] chm|11 years ago|reply
I bought Lanczos' book a month ago, I'm ~75 pages in (got other stuff to do). I will give SICM a try. I've just installed the 'ScmUtils Mechanics' package to accompany the book.

How can the code be difficult to get to work if he ships the required package with the book?

[+] bandrami|11 years ago|reply
VPM is in my read queue. His "Linear Differential Operators" was the best math book I read in years so I'm looking forward to it.
[+] _tqr3|11 years ago|reply
I cannot recommend 'The Society of Mind' enough. This was my first book before diving into Cognitive Science. Although it is mostly psychology(i.e.speculation), it is a brilliant book with insights and ideas.
[+] dnt404-1|11 years ago|reply
Why do find psychology to be speculation? Do they not use empiricism in their studies (maybe not all of them)?
[+] kleiba|11 years ago|reply
I bought the book some 15 years ago when my interest in AI was on its peak. I remember not being too impressed by it, but I always wanted to go back and give it a second try, especially since I cannot really remember the reason I didn't like it too much. I believe it was that I found some of the earlier ideas (every page basically describes one idea) not totally convincing, or maybe I just wasn't able to follow the later ones?
[+] nichochar|11 years ago|reply
I'm confused, you recommend it? Or you don't
[+] abc_lisper|11 years ago|reply
Quantum Computing since Democritus in high school reading list is very heavy. I have had Theory of Computation class in college and I can't read 20 pages of that book.
[+] derefr|11 years ago|reply
On the other hand, if you treat each page, each statement as something you have to completely internalize before moving onto the next page—including looking up all the prerequisite topics recursively on Wikipedia or in other texts—you might just end up teaching yourself up to college-level math while still in high school.

(I didn't do this myself with QCD, but I very nearly did it with SICP in middle school.)

[+] madars|11 years ago|reply
To provide a second opinion: for me it was probably one of the best books I read last year -- extremely lucid writing and very lively. I think I would have loved it in high school.
[+] Strilanc|11 years ago|reply
QC since Democritus is a weird mix of textbook and popularization; I think you could absolutely read it without understanding the details and still enjoy it. You won't get as much, but you'll still get something.

I didn't understand much of algorithms or quantum computing when I first read the lecture notes the book is sourced from [1]. Was still worth it.

1: http://www.scottaaronson.com/democritus/

[+] pjungwir|11 years ago|reply
I'm reading QCsD right now and loving it. But in high school? That sounds crazy. It'd help a lot to already understand Godel's proof, big-O notation, and P-vs-NP. Also relativity and quantum mechanics. And maybe some group theory.
[+] randomnumber53|11 years ago|reply
I'm a current HS senior who took a Theory of Computation class the year prior, and I got a few chapters into QCSD before realizing that I needed to learn some more about complexity theory before I read that book. I'm planning on trying again once the summer begins.

Now I'm about half-way through Godel, Esher, Bach, and I have to say that GEB and QCSD feel similar, with an overlap not only in theme but also in genre and style.

[+] selimthegrim|11 years ago|reply
It's not any heavier than GEB, and they will probably get more out of it. My picks in there would be Lanczos, Heinlein, and Levy, and SICP and SICM.
[+] peregrine|11 years ago|reply
I think he meant emphasis on "High" meaning high schooling. Not "high school"
[+] gshrikant|11 years ago|reply
Has anyone read the probability text mentioned in the list - Probability: The Logic of Science by Jaynes?

It looks like the text is freely available; I skimmed through the first chapter and it makes sense to me so far (I don't know how long that would hold true). I've been looking for a basic probability text for some time now, nothing too heavy but something to compensate for not having taken enough math in college.

[+] baddox|11 years ago|reply
Interesting to see Stranger in a Strange Land on his list. It shows up quite often on top lists of sci-fi books and Heinlein books. I'm halfway through it, after reading The Moon is a Harsh Mistress, and Stranger in a Strange Land is certainly the weaker book so far in my opinion.
[+] dublinben|11 years ago|reply
As I struggle to wade through it, I wonder why it was ever as popular as it once was. What is it about this book that make so many people recommend it?
[+] tjl|11 years ago|reply
My problem with Stranger in a Strange Land is it kind of falls apart around halfway to 2/3rds of the way through the book. The ending is pretty weak (as is most of Heinlein's endings). But, I found the first half of Stranger in a Strange Land to be excellent. In contrast, The Moon is a Harsh Mistress is a solid book all the way through. Also, a later book has a nice, little tie-in to it.
[+] iamcurious|11 years ago|reply
Don't hurry, wait and you will grok it in time.
[+] rurban|11 years ago|reply
KAM: Automatic Planning and Interpretation of Numerical Experiments Using Geometrical Methods

  * By Kenneth Man-Kam Yip, 1989
  * Coolest PhD thesis ever!
  * Solve problems using graphs.
  * So cool!
This caught my interest: http://dspace.mit.edu/handle/1721.1/7025

It is indeed one of the coolest papers and programs ever. KAM is a smart ODE solver, written in ZetaLisp on a Symbolics. It analyzes 2D pointsets created by any 2d equations, esp. non-linear ones. Typically a system of ordinary or partial differential equations, with a set of boundary and initial conditions. A typical non-linear physical system. It creates MST's (Minimal spanning trees) of the calculated points to get the shape and number of curves, to see the number of clusters (checking the distance of the curves), and if the curves are linear or space filling. Then the phase space is searched for initial states and end conditions, and to get useful summaries. It cannot do shape matching though, so repetitions and mirroring are not detected as such.

The goal is to get high-level descriptions of the model and the numerical dataset, and at which parameter ranges and conditions the system falls into chaos. Chaotic systems are bad for predictability but mostly good for engineering purposes.

[+] erhupisg|11 years ago|reply
Robert McIntyre is a wizard in his own right. He has taken the prowess of his mental faculties to the extreme, even mastering the art of bioluminescence.
[+] kirpekar|11 years ago|reply
Heavy list, I've read a few, but skimmed through most of these.

I'm certain only a handful of people have read all these books completely.

[+] jeffreyrogers|11 years ago|reply
Do people actually read all the books they recommend? I often tell people books are good, esp. books on some mathematical topic, without having read the entire thing myself, just selected parts as my inclination takes me. In fact, there are almost no textbooks I've read straight through.
[+] abecedarius|11 years ago|reply
On The Connection Machine: "Beautiful thesis, though it doesn't tell you anything you can really do today."

I don't understand: is data-parallel computing on a GPU much worse somehow? Or is it that there are better sources to read about data-parallel algorithms?

[+] sedachv|11 years ago|reply
> is data-parallel computing on a GPU much worse somehow?

OpenCL is a very awkward way to do vector processing - everything is hard-coded to an abstract model of a typical consumer GPU memory hierarchy. CUDA is even worse with a ton of versions all having different limitations according to what the Nvidia chips can do.

It's awkward to do a lot of SIMD tasks on GPUs. The Connection Machine was a general-purpose SIMD originally designed for parallel graph algorithms.

OpenCL looks like what the Connection Machine C* language might get macroexpanded into prior to compilation: http://people.csail.mit.edu/bradley/cm5docs/CStarProgramming...

[+] prestonbriggs|11 years ago|reply
Yeah, data-parallel computing on a GPU doesn't really approach what Hillis was aiming for. Check especially CM Lisp; great stuff.
[+] mark_l_watson|11 years ago|reply
Great list. I had misplaced my copy of the Connection Machine. So glad to have access to the PDF. Thanks!
[+] bcbrown|11 years ago|reply
I really enjoyed Time's Arrow and Archimedes' Point, by Huw Price.