Reading Guide To AI Design & Neural Networks?

Raistlin84 writes "I'm a PhD student in theoretical physics who's recently gotten quite interested in AI design. During my high school days, I spent most of my spare time coding various stuff, so I have a good working knowledge of some application programming languages (C/C++, Pascal/Delphi, Assembler) and how a computer works internally. Recently, I was given the book On Intelligence, where Jeff Hawkins describes numerous interesting ideas on how one would actually design a brain. As I have no formal background in computer science, I would like to broaden my knowledge in the direction of neural networks, pattern recognition, etc., but don't really know where to start reading. Due to my background, I figure that the 'abstract' theory would be mostly suited for me, so I would like to ask for a few book suggestions or other directions."

Comments

PDP

[kahizonaki]

Parallel Distributed Processing (both books) by Rumelhart, McClelland, and the PDP research group, 1986. "THE" classic neural network resource--and still somewhat relevant.

Re:PDP

[babbs]

I prefer James Anderson's "An Introduction to Neural Networks". I think it is better suited for someone coming from the physical, mathematical, or neuro- sciences.

The Resistance

[Anonymous Coward]

Due to the possibility of a robot army rising up, I refuse to help.

AIMA

[omuls are tasty]

Artificial Intelligence: A Modern Approach by Rusell and Norvig is more or less the standard AI textbook and the book I'd suggest to get an overview of AI and its different methodologies. Mind you, it's over 1000 pages, but a very interesting read.

AI != design brain

[Kupfernigk]

There is a very big difference between AI - which is based on guesses about how "intelligence" works, and studies of brain function. I'm going to make a totally unjustified sweeping generalisation and suggest that one reason that AI has generally been a failure is because we have had quite wrong ideas about how the brain actually works. That's to say, the focus has been on how the brain seems to be like a distributed computer (neurons and the axons that relay their output) because up till now nobody has really understood how the brain stores and organises memory in parallel- which seems to be the key to it all, and is all about the software.

So my feeling is that the first people really to get anywhere with AI will either work for Google or be the neurobiologists who finally crack what is actually going on in there. If I wasn't close to retirement, and wanted to build a career in AI, I'd be looking at how mapreduce works, and the work being done building on that, rather than robotics. I'd also be looking as seriously parallel processing.

So my initial suggestion is nothing to do with conventional AI at all - look at Programming Erlang, and anything you can find about how Google does its stuff.

Russell & Norvig

[Gazzonyx]

In my AI class, last semester, we used Stuart Russell and Peter Norvig's Artificial Intelligence A Modern Approach, 2nd Ed.. It's fairly dry, but good for theory nonetheless. If you're a physics geek, it should be right up your alley; they approach everything from a mathematical angle and then have a bit of commentary on the theory, but never seem to get to the practical uses for the theory.

If you're in the US, send me an email and I'll send you my copy. They charge an arm and a leg for these books and then buy them back for 1/10 the price. I usually don't even bother selling them back.

machine learning resources

[Anonymous Coward]

Following Books are must have for machine learning enthusiasts:

Christopher Bishop
http://research.microsoft.com/~cmbishop/prml/

Richard Duda
http://rii.ricoh.com/~stork/DHS.html

There you will get an insight how machine learning methods (like neural networks, SVM, boosting, bayes classificator) work

for general AI (not so much in direction of statistical learning as the books above, but more into higher level learning like inference rules) I can recommend published work done by

Drew McDermott
http://cs-www.cs.yale.edu/homes/dvm/

Ask an Eliza

[MosesJones]

Question: Where can I find a Reading Guide to AI Design & Neural Networks

Answer: Why do you want to AI design & Neural Networks?

Question: Because I want to learn.

Answer: Will learn AI design & neural networks make you happy

Question: Yes

There you go. Now the question is whether Slashdot beats the Turing test on this one.