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Ask Slashdot: Best Way To Learn About Game Theory and AI?
xmojox writes "I would like to learn more about Artificial Intelligence and Game Theory. I know these are both large areas of study; however, my main interest is in how these affect decisions in the world. This would include politicians, business people, and general society. I'm not looking for a career or anything; this is just a personal interest of mine. Where are good places to start in these areas for somebody new to them? I'm aware of the Stanford on-line classes, but those don't work with my current schedule."
Grab a copy of Russell and Norvig. It's a nice survey, and a fairly easy read.
See: http://www.lenfisherscience.com/books/rock_paper_scissors.html
-bone up on your probability (continuous/discrete distributions, transformations, etc)
-grab a book on statistical decision theory like Parmigiani and Inoue or Berger (85).
-read Von Neumann/Morgenstern
PS: I don't reply to ACs.
Stanford offers this? Where? Just curious because I'd be interested in something like this. I am currently enrolled in the Database & Machine Learning courses. I wouldn't mind taking on more! :P
I haven't had much time to dig in yet, but I hear good things about Less Wrong from some friends who are into game theory, ai, and sociology.
Here's their front page blurb:
Thinking and deciding are central to our daily lives. The Less Wrong community aims to gain expertise in how human brains think and decide, so that we can do so more successfully. We use the latest insights from cognitive science, social psychology, probability theory, and decision theory to improve our understanding of how the world works and what we can do to achieve our goals.
Stop-Prism.org: Opt Out of Surveillance
I'm aware of the Stanford on-line classes, but those don't work with my current schedule
Why? You can just watch the videos instead of doing the homework, or watch them sometime later and do the homework then.
But if you really had any interest you would be shifting around everything else, including sleep, to take fullest advantage of these classes in real time.
"There is more worth loving than we have strength to love." - Brian Jay Stanley
Buy a good book. I have two (one when I took it in university, and another I purchased later). For a good introduction: try a cognitive psychology course. I took it along with AI, and there was 1 other guy doing both that semester. We both agreed that apart from terms, you study for one and its like studying for both. They aren't of course the same, but the follow similar themes. Example: my Psych prof. asked the class to try and understand the missionaries/cannibals problem. "Just try to work the problem and see if you can figure it out. It represents a type of problem where you have to backtrack to get a proper solution". The next day, I got the same problem in CS, but it sounded more like this "You are required to write three programs showing the computer solving this missionaries/cannibals problem using depth first, breadth first, and best first search trees. Use alpha-beta pruning to speed the search. There was another program and some other problems as part of that weeks assignment. You could do it in C using multi-linked lists, but we used either prolog or (mostly) common lisp (pronounced lithp). Make sure the AI texts include predicate calculus, rules of inference, and modus tolens, modus ponens, introduction, elimination and universal instantiation.
Below is Stanford's Online courses.
http://see.stanford.edu/see/courses.aspx
There are a number of Ai related courses.
Not sure if they'll have anything, but worth a shot if you haven't looked here. http://ocw.mit.edu/index.htm
The Open Yale Courses has a well-curated and complete introduction to Game Theory that I strongly recommend: check it out! The Problem Sets, Syllabus, along with videos and transcripts are all available.
http://oyc.yale.edu/economics/game-theory
I purchased a course from "The Great Courses" on DVD last year (thegreatcourses.com), the topic of which was Game Theory. I've enjoyed the first half of the course, but haven't completed it. Unfortunately whenever I get time to go back to it, it has been long enough that I tend to start back at the beginning and watch the entire course over.
Uh, sure .... you go next and take my turn too.
Start with the Stanford course given on-line that start in a few weeks:
http://www.ai-class.com/
Read perceptrons, I'm sure a copy exists in your local college library.
I guess he knows something about using his time, after all, since he didn't answer you.
AHAHAHAHA oh snap!
As for gameThe Yale online course is excellent (pitched at an undergraduate level). A very good game theory book for the non-academic would be The Art of Strategy by Dixit and Nalebuff. More advanced introductions include Gibbons (1999) or Osborne (2003)
After you go thru the usual stuff (Intro to AI, on-line courses, et al)
Game Theory and Decision Theory in Agent-Based Systems ISBN 978-1-4020-7115-7
Game Theory: Analysis of Conflict ISBN 978-0674341166
Hope this helps.
One possibility here is of course that the original poster knows that the field is quite large and isn't interested in studying it intensely for several years. In that case it can be good to ask those who already have studied the field for pointers to figure out just which things are most essential to learn about, which books are likely to be most useful and such things. Basically, the original poster may just be trying to avoid wasting his/her time studying more or less irrelevant parts of the field (anyone who has ever gone through a few college courses in a technical field should know what I'm talking about here, there are plenty of textbooks out there that imply pretty heavily that specific peripheral details are somehow core concepts when in reality you could spend a day or two on them and learn all you'll reasonably need to know about them, I myself have a book somewhere in storage which confused me to no end when I was in high school, it went on for page after page after page about linked lists like they were the only thing that mattered to computer science when it could've just explained the concept, what they were good for and then moved on).
Greylisting is to SMTP as NAT is to IPv4
Read Artificial Intelligence: A Modern Approach, 3rd edition. It's supposedly the most-used AI textbook in the world.
It's weak on the biologically inspired methods (genetic algorithms, neural networks, fuzzy logic), but very solid in "Good Old Fashioned AI" (GOFAI) and some of the decision-making procedures from other fields such as economics.
If you don't have a background in CS, you'll need to work through a book on discrete math first.
Sheesh, evil *and* a jerk. -- Jade
http://lmgtfy.com/?q=ocw+game+theory
http://lmgtfy.com/?q=ocw+ai
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Read "AI : A Modern Approach 3rd edition" - it will give you a holistic and in-depth perspective. I think chapter 14 or 15 covers some of game theory.
For game theory specifically, read "Game Theory, a short introduction" , by the aptly named Ken Binmore - very succinct.
Central planning doesn't work nearly as well as decentralization of knowledge does.
The best way to learn is to do it. Choose a "game" and try to solve it with some different approaches. I say "game" with quotes because the game you pick should definitely not be a game which a normal adult would choose to play, but something very young children would play, or a heavily simplified variant of a full game. Something like Tic-Tac-Toe or RPS.
RPS seems trivial, but it's actually a very interesting game to study. It's an easy-to-understand example of how a Nash equilibrium strategy doesn't always produce an optimal outcome. The equilibrium strategy is to choose between the three moves at random, but you can't naively use the strategy because it offers no way of taking advantage of weak opponents, such as an opponent that favors a particular move or a pattern of moves. Computer RPS tournaments will always include a variety of bots that are predictably weak in various ways, to separate out the good bots that are capable of using these weaknesses.
Another simple game you could experiment with is Leduc Poker. Leduc Poker is another matrix game, and it's simple enough that you can easily compute the Nash equilibrium (which, remember, is not necessarily optimal, but it's a good starting point) or iterate over the entire game tree. You could also use a similar subset of poker to experiment with more advanced techniques - e.g. minimax and alphabeta pruning, or maybe Monte Carlo Tree Search (I can't guarantee that MCTS would work for poker, I'm not sure it's ever been done, but it might be interesting to try.)
If you are interested in decision making in everyday live perhaps game theory is the more relevant subject to study. AI has always been arcane in a loveable sort of way whereas game theory is mostly applied mathematics. Perhaps you can benefit from my method: I went to our library (I work at at university, so your mileage may vary) and looked through a couple of books on game theory until I found that two that nicely complemented each other. It's very hard to give advise about introductory sources without knowing what you know and how you learn best.
Also, as a general method of learning new subjects: Try to think about things you already know in terms of the new theory. In your case that's probably what you want to do in the long run anyway given your stated motivation for learning those subjects.
Some think that artificial intelligence seeks to emulate the real intelligence of humans. But most of it is just software, and has little to do with real intelligence.
There are certain problems that AI can solve, but those solutions are not "intelligent" but rather are merely "formulas" programmed by intelligent people (computer scientists).
We get excited when these formulas emulate what a real person might do, and when we can hide the underlying machine, but that is not to say we know how people think or even how we are implemented. We are just getting better at programming.
There are some great advancements in cognitive science, and the more we discover about how the brain works, the less it looks like it could be run by any "code". No intel inside. The brain is an organ that grows and dies, and takes its memories with it. If anything, it programs itself.
That is not to say there haven't been advancements in AI. It too is incredibly useful.
A good place to start: ... and wikipedia of course...
http://www.ted.com/search?q=brain
http://www.ted.com/search?q=artificial+intelligence
how about a nice game of chess?
This is a good book.
There is a free Stanfrod University AI-Class this fall. In this fall's edition of it, the two legendary teachers are letting the whole world participate.
It's been a featured story on Slashdot a couple of months ago.
You still have time to sign up and join the class which starts in October
http://www.ai-class.com/
Not to belittle your choices, but this is a VERY complicated subject. My favorite introductions to game theory are, "The Compleat Strategyst" by Williams, and, "Strategy in Poker, Business and War" by McDonald. These are not trivial books, but they are easy reads into the uses of Game Theory.
After that, you get into some Math. Read anything you can on Probability and Risk; know your Statistics and Calculus. Much of what you are looking for will be found under the subject "Decision Theory."
I say study Economics because this is where political and economic scientific thought is making the greatest gains at this time. Game theory has a lot to do with "payoff" and Economics is a fertile field for studying payoffs. (So is Political Science, and there some good laboratories in, say, Afghanistan, Mexico and Chicago. But that's a slightly different, pragmatic, field of study.)
My favorite definition of "politics" is: "The behavior of vying for scarce rewards." This is almost exactly a definition for Economics. At one time Economics was thought to be a sub-level of politics; it now seems the opposite is true.
Hayak pretty much proved that economic behavior cannot be quantified because of the complexity. What is useful is deriving principles of actions under a variety of conditions to provide maximum payoffs, for the most people, under the widest variety of conditions. (An alternative course is to try to derive the largest payoffs for the fewest people under specific conditions.) AutoDesk used to have an Artificial Life laboratory that you could manipulate to learn about Genetic Algorithms and other AI behavior. Context-dependent AI can be learned through developing Neural Nets. Some of the guys I've talked to at Carnegie Mellon in the Quantitative Economics studies have warring economic artificial hybrid GA/Neural Nets, and the observations are pretty interesting.
If it was simply a matter of rational decision making, optimum economic strategies could probably be described and tested in a much smaller AI field. However, politics and economics are burdened with mis-perceptions, human values, and stubborn beliefs. This is a big field, and you should be able to enjoy it as a hobby for the rest of your life without running into a limit of learning.
"The mind works quicker than you think!"
Because if the original poster was interested in computer games, then he might think "game theory" would help him making games. Which is as much the case as quantum mechanics helps with fixing a car. ^^
In case he really meant computer games and the theory about them:
"The Art of Game Designâ by Jesse Shell. 'nuff said.
For AI, I would suggest enrolling into the Stanford Artificial Intelligence Course. It will start on October 10th this year and lasts until December (I think).
Ubuntu is an African word meaning 'I can't configure Debian'
First, read up on Braitenburg Vehicles and The Selfish Gene, by Richard Dawkins. Dawkins is something of a deity in the annals of evolutionary biology and is worthy of worship :-p
Then read up on Neural Networks, start simple with a feed-forward with error backprop.
Then try your hand at some Temporal Difference Learning.
Then take a look at genetic algorithms, but it might help you to first understand the classic A* heuristic search algorithm. Genetic algorithms tend to be interesting search algorithms that are inspired by a genetic process, but they have little connection to the actual biological process for which they are named, so I am biased against them. This perception could just be a local cognitive minima that might be avoided with better training.
"Every time I see an adult on a bicycle, I no longer despair for the future of the human race." - H. G. Wells
Not knowing exactly what level of knowledge you're starting from... One of my first game purchases was Patton Versus Rommel, which included some artificial smarts. The liner notes included a reference to his second book The Art of Computer Design, [PDF] and based on the context, I hoped it might include at least introductory pointers to game AI. Nope. There's also Chris Crawford on Game Design, [Google Books]. It does include some high level designs, which may or may not be what you're looking for.
Luke, help me take this mask off
I've been in the same boat as the OP. I did research it and its wide and varied.
If you don't understand the question, why the hell did you post an answer?
Mod: Troll
Are available here.
Happy studying.
Hey xmojox, if you want to understand human decisions, you might be better off looking into psychology. Dan Gilbert had a great talk on TED on happiness and human decision making: http://www.youtube.com/watch?v=LTO_dZUvbJA
Currently doing my PhD in Compuer Science on game theory related topics. I recently ordered this book to learn something on behavioural studies: http://press.princeton.edu/titles/8901.html I really enjoyed reading the pages you can find online.
May I suggest the following book:
Multiagent Systems
Algorithmic, Game-Theoretic, and Logical Foundations
Yoav Shoham
Stanford University
Kevin Leyton-Brown
University of British Columbia
http://www.masfoundations.org/index.html
If you really have no patience for philosophy, try Game Theory for Applied Economists by Robert Gibbons instead. ;-)
John Maynard Smith's Evolution and the Theory of Games is accessible and indispensable.
Less technical works that explore the implications of the theory in fascinating ways include The Evolution of Cooperation (the book that first got me interested in the subject) and The Complexity of Cooperation by Robert Axelrod, and anything by Brian Skyrms.
Here is the complete Youtube playlist for the Yale course "Game Theory", lectured by Ben Polak. 24 lectures in total, about 1 h 15 min each.
Course description: This course is an introduction to game theory and strategic thinking. Ideas such as dominance, backward induction, Nash equilibrium, evolutionary stability, commitment, credibility, asymmetric information, adverse selection, and signaling are discussed and applied to games played in class and to examples drawn from economics, politics, the movies, and elsewhere.
I have had the intention of watching through this, but haven't had the time after the first few lectures. The material is recommended, though.
http://www.youtube.com/playlist?list=PL6EF60E1027E1A10B
Good game theory books I keep on my shelf:
Nonlinear Dynamics, Mathematical Biology, and Social Science (Santa Fe Institute Studies in the Sciences of Complexity Lecture Notes)
by Joshua Epstein
Westview Press
ISBN: 9780201419887
(if you know enough math for partial differential equations, this book is a must-have, since it's directly applicable to mathematically modelling open source software projects)
The Evolution of Cooperation
by Robert Axelrod and William D. Hamilton
Paper: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.147.9644&rep=rep1&type=pdf
Book: ISBN 0-465-02122-2
Perspectives on Adaptation in Natural and Artificial Systems
Basic Books
ISBN: 9780195162929
The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration
by Robert Axelrod
Princeton University Press
ISBN 978-0691015675
Game Theory and the Social Contract, Vol. 1: Playing Fair
by Ken Binmore
MIT Press
ISBN 978-0262023634
Game Theory and the Social Contract, Vol. 2: Just Playing (Economic Learning and Social Evolution)
by Ken Binmore
MIT Press
ISBN 978-0262024440
Analyzing Policy: Choices, Conflicts, and Practice
by Michael C. Munger
W. W. Norton & Company
ISBN 978-0393973990
Growing Artificial Societies: Social Science from the Bottom Up (Complex Adaptive Systems
by Joshua M. Epstein, Robert L. Axtell
MIT Press
ISBN 978-0262550253
See also:
http://www.santafe.edu/
http://www.youtube.com/user/santafeinst
The Brookings Institute is also active in this area (it was their math that led most of the U.S. Cold War policy and kept everyone out of a nuclear exchange with the Soviets).
-- Terry
Why don't you try Yale's version... download it and look it when you want \o/
Yale Game theory
It is surprising that nobody suggested ai-class.com and ml-class.com - a large scale e-learning experiment which is gonna be conducted starting October by some of the best professors in that field (Peter Norvig, Thrun, etc.)
You are just in time !!
MIT has tons of material on AI, on their OpenCourseWare site, especially in the Electrical Engineering and Computer Science section.
I would suggest the book "Algorithmic Game Theory" (by Nisan, Trados, Roughgarden and Vazirani (Cambridge University Press)) to be found on Nisan's home page from a simple google search.
On AI, I would suggest the Russel and Norvig "AI: A modern approach"
Hi, I would like to learn everything about [insert topic]. Do you have any suggestions about how I can do this? I don't really want anything that involves reading, listening to lectures, or in fact any kind of extra work. I've tried sleeping with the textbooks under my pillow but this doesn't really work for me.
Your suggestions are appreciated.
I'll get shot down in flames for this, but it's a geek fallacy to think that you can understand "politicians, business people, and general society" through "Artificial Intelligence and Game Theory".
To understand politicians, study politics.
To understand business people, study business.
To understand society, study sociology.
Of course, to understand Artificial Intelligence and Game Theory, then study Artificial Intelligence and Game Theory.
Tank, I need a program for AI and Game Theory... Hurry!
Set your phasers on "funky"!
"I would like to learn more about Artificial Intelligence and Game Theory. I know these are both large areas of study; however, my main interest is in how these affect decisions in the world. This would include politicians, business people, and general society. I'm not looking for a career or anything; this is just a personal interest of mine. Where are good places to start in these areas for somebody new to them? I'm aware of the Stanford on-line classes, but those don't work with my current schedule."
Do you really understand how unwise it is to put those words together in that manner? Don't interfere.
Shh.
I found this an enjoyable - if not especially in-depth - undergraduate-level introduction. I recommend it if you're new to game theory.
http://oyc.yale.edu/economics/game-theory/
If you're serious, the bible of game theory is:
MasCollel, Winston, and Greene's text on Microeconomic theory, or MCGW,
You will need to be advanced in mathematics and comfortable reading it.
I'm a PhD, student in economics, and completed game theory last semester, finished the prelim with the highest score in the class.
I haven't seen anyone post it yet, but if your interest is in human-like intelligence, read an AI critic like Searle.
What you ask will involve years of study... you can't learn this reading some "A.I. book" from Barnes and Nobles....
It's like asking, I don't want to go to law school, but I would like to become a lawyer....
I don't understand questions like these.
No shit, you empathic wonder. Looks like the world is binary for you, Mr. Douchebag. May God have mercy on any kids you might have someday.
Read Avinash Dixit's Thinking Strategically to get started. It's a great book which does not use much math and can make for light reading and a great start.
Agreed, this is a valuable and approachable intro to game theory! I've been studying with it, too.
Games People Play: Game Theory in Life, Business, and Beyond , a 12-hour course taught by Professor Scott P. Stevens. US$254.95.
M.I.T. had two 150th birthday conferences on A.I. this year. This would give some ideas on the state of the art and the players. Its not a systematic, pedagogical presentation.
Actually I am only half kidding! I was interested in this myself recently and found that there is a Yale proff teaching game theory that puts his lectures on youtube. I sat through two lectures on Nash Equilibrium a few months back: http://www.youtube.com/watch?v=7oASpaBdDMs
Course it couldn't hurt to get a text book, but, it would be trivial to lookup the required books for these or other similar classes, and go buy them at any college book store. Just walk right in and buy them, or find them online.
Is it the best way? Dunno.... but its a resource that you can use.
"I opened my eyes, and everything went dark again"
AI is an entirely fraudulent field of study so you might as well study time travel or cold fusion for all the good it will do you.
It is fascinating - but Game Theory abstracts most of the "read world" out of the real world problem in order to investigate specific limited rule set engagements. This does not really help when trying to understand how humans actually think and make decisions. Search ted.com for irrationality and decision making and watch some of those video's before you invest too much of your time. Also, an interesting book is Black Swan - although you may decide to give up after reading it, it supplies the "anti perspective" if you will...
The Compleat Strategyst is an old but very good (not too mathematical) introduction to pure game theory.
Winning Ways for Your Mathematical Plays is a great series of books on the mathematics of games.
For AI, see previous reco's. For my money you can't go wrong with Russel/Norvig, unless you are looking specifically for AI that plays games.
You can watch a very nice series of lectures on game theory from Yale at http://www.academicearth.org/courses/game-theory
You can also download that same set of lectures from http://oyc.yale.edu/economics/game-theory/
I watched the whole thing and really enjoyed it.
Games, Strategies, and Managers: How Managers Can Use Game Theory to Make Better Business Decisions
by John McMillan
http://books.google.com/books?id=c24CPx9R0PYC&printsec=frontcover&dq=games+managers&hl=en#v=onepage&q&f=false
Its definitely a subset of AI, but if you are interested in Machine Learning then you should check out the Deep Learning Tutorials. They cover most of the building blocks of "Deep Learning", which you can think of as the new wave of Artificial Neural Networks. The tutorials include complete theoretical (and mathematical) descriptions of the model, as well as Python/Theano implementations. Pre-requisites would be a good math background (first year calculus should suffice), basic probability theory and coding in Python/numpy. You can learn Theano as you go along.
Its definitely a subset of AI, but if you are interested in Machine Learning then you should check out the Deep Learning Tutorials [deeplearning.net]. They cover most of the building blocks of "Deep Learning", which you can think of as the new wave of Artificial Neural Networks. The tutorials include complete theoretical (and mathematical) descriptions of the model, as well as Python/Theano implementations. Pre-requisites would be a good math background (first year calculus should suffice), basic probability theory and coding in Python/numpy. You can learn Theano as you go along.
ps: sorry for the repost, forgot to log-in beforehand.
A million monkeys and this is the best sig they could come up with...
One easy technical book I enjoyed was Malanie Mitchell's Genetic Algorithms. She also wrote a book on Complexity, but I didn't find this enjoyable. A hugely fun book on these topics (perhaps becoming a little dated) is Aritificial Life by Stephen Levy.
Between work and other studying obligations (which my job depends on) ... I can't commit myself to that kind of structure.
Why not try? There is NO DOWNSIDE to signing up. It's free!!! You can see if there's any way to make it work. You can see if even the light version would work, or in fact if the topic really interests you after you see what it involves. The videos are put up once a week and you watch them whenever.
Why should you try? Because you will learn, and retain, much more if you are working problems, asking questions, and seeing what questions over people ask. Sign up if only to ghost in on the questions asked which may spark new ideas or interests.
The class is free; it's madness not to sign up and try to make it work. Chances are you have more time than you think.
"There is more worth loving than we have strength to love." - Brian Jay Stanley
http://www.ai-class.com/
how is babby formed?
"The Predictioneer's Game" by Bruce Bruno de Mesquita is an overview of the authors use of game theory and statistical predictions of behavior (for profit, no less). He has a Ph.D. in political science, covers a few historical situations and bangs out some predictions. It is not heavy on the math, but would take a few afternoons to plow through.
Sounds like you are interested in Multiagent Systems. I am current taking a graduate course in MAS theory at Waterloo. Here is the book we use; it's free online http://www.masfoundations.org/index.html. It's an excellent book; the details and the high level ideas are broken apart nicely, such that if you want to go balls deep you can, but if you just wan't the high level ideas you can grab those too.
I have it still. I think it was called "Predicting International Events." (Predicting Global Events?) I could find it for you and I am sure he has continued his research. It was based on an artificial intelligence "bidding system" based on priorities. Made me immediately think of Asimov's "Foundation" series.
Jeff Hartman
This is a hard-work. One of my friends is studing in this. But it is still a long way to learn .
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