Stuart Russell

So my program never beat me at chess.

I actually wrote the program at Imperial College.

So I used to take the bus every Wednesday with a box of cards this big and shove them into the card reader.

And they gave us eight seconds of CPU time.

It took about five seconds to read the cards in and compile the code.

So we had three seconds of CPU time, which was enough to make one move with a not very deep search.

And then we would print that move out, and then we'd have to go to the back of the queue and wait to feed the cards in again.

How deep was the search?

No, I think we got an eight move, a depth eight with alpha, beta, and we had some...

tricks of our own about move ordering and some pruning of the tree.

But you were still able to beat that program?

Yeah, yeah.

I was a reasonable chess player in my youth.

I did an Othello program and a backgammon program.

So when I got to Berkeley, I worked a lot on

what we call meta reasoning which really means reasoning about reasoning and in the case of a game playing program you need to reason about what parts of the search tree you're actually going to explore because the search tree is enormous or you know bigger than the number of atoms in the universe and

And the way programs succeed and the way humans succeed is by only looking at a small fraction of the search tree.

And if you look at the right fraction, you play really well.

If you look at the wrong fraction, if you waste your time thinking about things that are never going to happen, the moves that no one's ever going to make, then you're going to lose because you won't be able to figure out the right decision.

So that question of how machines can manage their own computation, how they decide what to think about, is the meta-reasoning question.