Ask Slashdot: Best Way To Learn About Game Theory and AI? 152
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."
statistical decision theory (Score:5, Interesting)
-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
Less Wrong (Score:3, Interesting)
I haven't had much time to dig in yet, but I hear good things about Less Wrong [lesswrong.com] 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.
The best way to learn is to do it (Score:4, Interesting)
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:statistical decision theory (Score:4, Interesting)
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.