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."

Comments

Russell and Norvig

[Anonymous Coward]

Grab a copy of Russell and Norvig. It's a nice survey, and a fairly easy read.

statistical decision theory

[ThorGod]

-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

Re:statistical decision theory

[Slugster]

-read Von Neumann/Morgenstern

I have the Von Neumann/Morganstern book. It is very heavy reading, Rain-Man level stuff. Unless you're rich or its really cheap, it's a good idea to thumb through a copy before buying.

On the other [fuffy] end of the spectrum is Prisoner's Dilemma by William Poundstone. A 1-2 hour read suitable for teens, with no difficult math and a lot of real-world examples.

How do they not work??

[SuperKendall]

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.

Re:How do they not work??

[elsurexiste]

Why? You can just watch the videos instead of doing the homework, or watch them sometime later and do the homework then.

Maybe xmojox isn't around a PC for hours, because of his/her job, and spend a few more hours commuting. Maybe he/she has no tablet that's easily carried. We are not to judge. If we don't believe what's telling us, we may as well think this question is just an attempt at trollling and stop wasting our times.

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.

Worst. Advice. Ever. If you don't sleep at least six hours, you'll notice. It isn't sustainable.

On topic: Check Wikipedia's page for Game Theory and go to the citations. There you'll find a few books and other resources you can read.

Russell & Norvig

[Black Parrot]

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.

The best way to learn is to do it

[Unoriginal_Nickname]

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.)

Re:Stanford AI and Game Theory?

[Needlzor]

www.ai-class.org, by Sebastian Thrun and Peter Norvig

You might try Economics instead.

[meburke]

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.

Game Theory: A Critical Introduction

[mrogers]

The best technical introduction to game theory I've come across is Game Theory: A Critical Introduction by Shaun P. Hargreaves-Heap and Yanis Varoufakis, which introduces the most important concepts while placing them within their philosophical context (for example, to what extent is it reasonable to regard humans as the kind of agents assumed by game theory?). I've been studying game theory for years and wish I'd read this book a long time ago.

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.

Good game theory books I keep on my shelf:

[tlambert]

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

Consciousness

[Smallpond]

I haven't seen anyone post it yet, but if your interest is in human-like intelligence, read an AI critic like Searle.

Game theory

[rajats]

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.