Would you mind if I edited this post in order to express more strongly that the vast majority of this reading is not required to keep up with the vast majority of LW posts?
The dependency graphs of Eliezer's posts are an often-overlooked resource. I don't see them linked anywhere on the wiki either.
Nice idea, thanks for taking the time to compile these resources!
A few thoughts:
This would be easier to follow if the links in each section were ordered roughly from easiest to most challenging.
The length of this list is going to intimidate some new readers. One could productively add to the LW conversation after understanding a small fraction of these references. You should make it clear that these aren't prerequisite.
Some of the entries seem only tangentially related to LW (e.g. Haskell, Go).
The "Key Concepts" section might be better
Very nice. My only suggestions are to (1) add a biology section, for people who haven't quite grok'd how the brain is an organ, and (2) tweak the physics section so that it doesn't lead off with quantum physics, if necessary by making two physics sections. The notion that the world's fiddly bits behave according to mathematical laws is neither obvious nor self-explanatory, and starting to explain this notion by reference to casually observable phenomena (rocks, light, magnets, water) rather than deeply confusing and occasionally controversial phenomena (quarks, neutrinos) is a really good idea.
Excellent free lecture series on quantum mechanics from Oxford's undergraduate course. Consists of 24 one-hour lectures. Course material, solutions, and even the PDF of textbook is free.
Want to note: I noticed the category "memetic hazard" and started immediately skimming the page to find everything labeled as such. Something is wrong with my reasoning here—
It wasn't the worst impulse to follow after all, since the category means something like controversial or fictional. Except... "memetic hazard" is a meaningful warning. I would prefer it keeps its value as a signal.
Update 2010-11-11
In information theory, the link to 'Information Vs. Meaning' is broken.
Please fix it, it sounds useful :)
Update 2010-12-02
In the linguistics section, Trask's book should be marked as "easy." It's short and very readable, and assumes almost no background knowledge. (But despite that, provides an informative and well-balanced introduction to the field.)
Edit: Also, a draft of Jaynes's book is available for free online, but the list contains only an Amazon link.
Recent updates:
Marks with similar-looking letters (F and E) in light colors look bad on white background (hard to notice). Use contrasting darker colors (if at all) and more distinct text labels, maybe also bolded.
Absolutely the best resource for learning computer programming that I've come across. Highly recommended for beginners.
All the M labels could use explanations, but in particular, why is A Fire Upon the Deep controversial?
Update 2010-10-29
Update 2010-10-21 #1
Update 2010-10-20 #1
I added the dependency graphs of Eliezer's posts as suggested by AngryParsley and in the course of it added a new category called LessWrong Overview.
The Leading Go Software (PC, Mac, iPhone, iPad)
There is as of yet no Mac version, just a placeholder page.
The first 3 chapters of Jaynes' "Probability Theory: The Logic of Science" is available at: http://bayes.wustl.edu/etj/prob/book.pdf
Also, here's a copy of his unpublished book (pdf link at bottom): http://bayes.wustl.edu/etj/science.pdf.html
Are you sure Diaspora should be marked Easy?
I tried to get a fairly intelligent, friend who's interested in science (generally, not necessarily any specific domains covered in the book) to read it and she gave up within about half an hour.
I (a layman, but well-acquainted with the set of singularitarian memes that the book draws from) found that trying to visualize the physics made my head hurt, even with the accompanying illustrative java applets at the author's website.
It also might be valuable to link to those (there are probably some for Permutation Cit...
Not sure how much it fits here, but http://docartemis.com/brainsciencepodcast/2010/09/bsp70-lillienfeld/ is a reasonable intro + reference collection on some mental blindspots
I only wish that this post had been in a more visible place, so I could have found it before now. This seems like it will be very useful. Thank you for compiling.
Update 2010-11-10
Update 2010-11-03
More information here: http://lesswrong.com/r/discussion/lw/30t/anthropic_principles_agree_on_bigger_future/
Update 2010-11-01
I added a lot of new books, e.g. Concrete Mathematics: A Foundation for Computer Science or Principles of Neural Science, and integrated the external list of links on Bayesian probability into the probability section.
For future updates I'll leave a comment giving the details of each update so everyone who has already read the whole list only has to read that particular comment for possible interesting new content.
http://en.wikiquote.org/wiki/Main_Page
A source for quotes (presumably checked for accuracy) which includes their contexts.
Update 2010-12-06
Update 2010-11-09
...Richard Bird takes a radically new approach to algorithm design, namely, design by calculation. These 30 short chapters each deal with a particular programming problem drawn from sources as diverse as games and puzzles, intriguing combinatorial tasks, and more familiar areas such as data compression and string matching. Each pearl starts with the statement of the problem expressed using the functional programming language Haskell, a pow
Update 2010-11-08
It is a free book by David P. Williamson and David B. Shmoys, to be published in early 2011 by Cambridge University Press.
...Interesting discrete optimization problems are everywhere, from traditional operations research planning problems, such as scheduling, facility location, and network design, to computer science problems in databases, to advertising issues in viral marketing. Yet most interesting discrete optimization problems are NP-hard.
Zed Shaw has come out with Learn Python the Hard Way, intended to teach Python to absolute beginners, which looks promising based on a quick browse.
He also wrote a blog post How To Write a Learn X the Hard Way, about the writing principles behind the book.
Update 2010-11-02
Thanks goes to CarlShulman for pointing this out.
Update 2010-10-31
Update 2010-10-30
Update 2010-10-22 #1
Artificial Intelligence now has its own category including a sub-category for The Technological Singularity. The remaining Concepts have been moved to the Miscellaneous section as a sub-category.
AI grew too big and is too important as to be a mere subcategory of miscellaneous concepts.
I appreciate the labels, which are new since the last time I saw a draft. I recommend adding a summary break.
Perhaps a link to lukerog's the best textbooks on every subject.
Also, why no mention of the self-help aspects of LW?
A list of references and resources for LW
Updated: 2011-05-24
Summary
Do not flinch, most of LessWrong can be read and understood by people with a previous level of education less than secondary school. (And Khan Academy followed by BetterExplained plus the help of Google and Wikipedia ought to be enough to let anyone read anything directed at the scientifically literate.) Most of these references aren't prerequisite, and only a small fraction are pertinent to any particular post on LessWrong. Do not be intimidated, just go ahead and start reading the Sequences if all this sounds too long. It's much easier to understand than this list makes it look like.
Nevertheless, as it says in the Twelve Virtues of Rationality, scholarship is a virtue, and in particular:
Contents
LessWrong.com
This list is hosted on LessWrong.com, a community blog devoted to refining the art of human rationality - the art of thinking. If you follow the links below you'll learn more about this community. It is one of the most important resources you'll ever come across if your aim is to get what you want, if you want to win. It shows you that there is more to most things than meets the eye, but more often than not much less than you think. It shows you that even smart people can be completely wrong but that most people are not even wrong. It teaches you to be careful in what you emit and to be skeptical of what you receive. It doesn't tell you what is right, it teaches you how to think and to become less wrong. And to do so is in your own self interest because it helps you to attain your goals, it helps you to achieve what you want.
Overview
Why read Less Wrong?
A few articles exemplifying in detail what you can expect from reading Less Wrong, why it is important, what you can learn and how it does help you.
Artificial Intelligence
General
Friendly AI
Machine Learning
Not essential but an valuable addition for anyone who's more than superficially interested in AI and machine learning.
The Technological Singularity
Heuristics and Biases
The heuristics and biases program in cognitive psychology tries to work backward from biases (experimentally reproducible human errors) to heuristics (the underlying mechanisms at work in the brain).
Mathematics
Learning Mathematics
Basics
General
Probability
Math is fundamental, not just for LessWrong. But especially Bayes’ Theorem is essential to understand the reasoning underlying most of the writings on LW.
Logic
Foundations
Miscellaneous
Decision theory
Remember that any heuristic is bound to certain circumstances. If you want X from agent Y and the rule is that Y only gives you X if you are a devoted irrationalist then ¬irrational. Under certain circumstances what is irrational may be rational and what is rational may be irrational. Paul K. Feyerabend said: "All methodologies have their limitations and the only ‘rule’ that survives is ‘anything goes’."
Game Theory
Programming
Programming knowledge is not mandatory for LessWrong but you should however be able to interpret the most basic pseudo code as you will come across various snippets of code in discussions and top-level posts outside of the main sequences.
Python
Python is a general-purpose high-level dynamic programming language.
for Python Games! F
Haskell
Haskell is a standardized, general-purpose purely functional programming language, with non-strict semantics and strong static typing.
General
Computer science
One of the fundamental premises on LessWrong is that a universal computing device can simulate every physical process and that we therefore should be able to reverse engineer the human brain as it is fundamentally computable. That is, intelligence and consciousness are substrate-neutral.
(Algorithmic) Information Theory
Physics
General
General relativity
Quantum physics
Foundations
Evolution
Philosophy
General
The Mind
Epistemology
Levels of epistemic accuracy.
Linguistics
Neuroscience
General Education
Miscellaneous
Not essential but a good preliminary to reading LessWrong and in some cases helpful to be able to make valuable contributions in the comments. Many of the concepts in the following works are often mentioned on LessWrong or the subject of frequent discussions.
Concepts
Elaboration of miscellaneous terms, concepts and fields of knowledge you might come across in some of the subsequent and more technical advanced posts and comments on LessWrong. The following concepts are frequently discussed but not necessarily supported by the LessWrong community. Those concepts that are controversial are labeled M.
Websites
Relevant websites. News and otherwise. F
Fun & Fiction
The following are relevant works of fiction or playful treatments of fringe concepts. That means, do not take these works at face value.
Accompanying text: The Logical Fallacy of Generalization from Fictional Evidence
Fiction
Fun
Go
A popular board game played and analysed by many people in the LessWrong and general AI crowd.
Note:
This list is a work in progress. I will try to constantly update and refine it.
If you've anything to add or correct (e.g. a broken link), please comment below and I'll update the list accordingly.