Reddit reviews Introduction to the Theory of Computation
We found 14 Reddit comments about Introduction to the Theory of Computation. Here are the top ones, ranked by their Reddit score.
Used Book in Good Condition
In the theoretical field of complexity...
The 1979 version of Introduction to Automata Theory, Languages, and Computation by Hopcroft & Ullman is fantastic and used to be the canonical book on theoretical computer science. Unfortunately the newer versions are too dumbed down, but the old version is still worth it! These days Introduction to the Theory of Computation by Sipser is considered to be the canonical theoretical computer science text. It's also good, and a better "introduction" than H&U. That said, I prefer H&U and recommend it to anyone who's interested in more than getting through their complexity class and forgetting everything.
In the theoretical field of algorithms...
Introcution to Algorithms by Cormen, Leiserson, Rivest and Stein is dynamite, pretty much everything you need to know. Unfortunately it's a bit long winded and is not very instructive. For a more instructive take on algorithms take a look at Algorithms by Dasgupta, Papadimitriou and Vazirani.
Introduction to Algorithms by CLRS
TAOCP is a waste of time and money; it's more for adorning your bookshelf than for actually reading. Pretty much anyone who suggests TAOCP and is less than 55 years old is just parroting Standard Wisdom™.
Godel, Escher, Bach is a nice book, but it's not as intellectually deep in today's world as it was when first published; a lot of the memes in GEB have been thoroughly absorbed into nerd culture at this point and the book should be enjoyed more as a work of art than expecting it to be particularly informative (IMO).
If you're interested in compilers, I recommend Engineering a Compiler by Cooper & Torczon. Same thing as TAOCP applies to people who suggest the Dragon Book. The Dragon Book is still good, but it focuses too much on parser generators and doesn't really cover enough of the other modern good stuff. (Yes, even the new edition.)
As far as real programming goes, K&R's The C Programming Language is still unmatched for its quality of exposition and brevity, but these days I'd strongly suggest picking up some Python or something before diving into C. And as a practical matter, I'd suggest learning some C++ from Koenig & Moo's Accelerated C++ before learning straight C.
Sipser's Introduction to the Theory of Computation is a good theory book, but I'd really suggest getting CLRS before Sipser. CLRS is way more interesting IMHO.
It's an introduction to some of the major concepts in Computer Science theory. If you have no background in CS, and a bit of background in math (mid-undergraduate level) it's an enjoyable way to get exposed to a few concepts from CS theory.
If you're really looking to put your head to the grindstone and learn CS theory, there are better books though. I learned from M. Sipser's Intro to Comp. Theory.
P.S. I did walk away from it with a novice appreciation for Bach.
I'm quite a fan of Sipser's Introduction to the Theory of Computation: http://www.amazon.com/Introduction-Theory-Computation-Michael-Sipser/dp/053494728X
It's not a full-on algorithms book but formal models were always the most interesting part of theoretical computer science to me. vOv
Yes I took "Theory of Computation" as well. It's was one of those classes where I went where the average grade is an F and everything is just scaled up. It really kick my ass sadly. I think I took it the same semester as compilers as it was not a pre-req at my school.
This is the book we had I believe is: https://www.amazon.ca/Introduction-Theory-Computation-Michael-Sipser/dp/053494728X
Sipser's Introduction to the Theory of Computation is somewhat of a classic in the field. I just really hate his notation.
With all of Hofstadter's pseudophilosophical ramblings, Godel Escher Bach has more to do with Dianetics than with the field of computer science.
Anyway, why not actually get your feet wet? Good places to start are either algorithms or computability. DPV gives an easy introduction to the first topic, Sipser is the standard for the second (you don't need the latest version).
Michael Sipser's Introduction to the Theory of Computing is another good book on this topic. Very readable and short.
The goto theory book by Sipser.
Excellent for C programming.
Programming in general.
My favourite.
You can probably find all of these at a library.
Sipser's Introduction to the Theory of Computation is excellent. Amazon link. Doesn't entirely matter which edition you get.
I highly recommend Michael Sipser's Introduction to the theory of computation. I found it engaging enough that I actually read it in bed. Had to stop because it kept me from sleeping.
This book will get you started:
Introduction to the Theory of Computation https://www.amazon.com/dp/053494728X/ref=cm_sw_r_other_apa_EuBuxbYS2QXF3
But if your understanding of the foundations of math and logic are not strong, you may wish to begin with Language, Proof, and Logic by Barwise or a more historical treatment from the book, A Profile of Mathematical Logic by Howard Delong. For a bit more light-hearted and thought-provoking, read Godel, Escher, Bach: An Eternal Golden Braid.
To connect this material to philosophy of mind, get David Chalmers' introductory textbook.
The scope of your question does not fit nicely into a reddit comment. But if you request, I will go into greater detail.
Sipser on algorithms is the can't-go-wrong starting point. You can get an older edition cheap and it will be just as good.
Do the problems. Come back with questions.
Sipser's book is basically free on amazon if u buy used old editions. http://www.amazon.com/gp/aw/ol/053494728X/ref=olp_tab_used?ie=UTF8&condition=used
It basically just asks wut restricted types of computers can do. Like wut happens if u have a program but only a finite amt of memory, or if u have infinite memory but it's all stored in a stack. Or if u have infinite memory with random access.
Turns out lots of models r equal and lots r different and u can prove this. Also, these models inspire and capture lots of ur favorite programming tools like regex (= DFA) and parser generators (= restricted PDA) for ur favorite programming languages.