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CronoDAS comments on Say Not "Complexity" - Less Wrong
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Forgive me for latching onto the example, but how would an AI discover how to solve a Rubik's cube? Does anyone have a good answer?
I had the same problem.
I think it would need some genetic algorithm in order to figure out about how "close" it is to the solution, then make a tree structure where it figures out what happens after every combination of however many moves, and it does the one that looks closest to the solution.
It would update the algorithm based on how close it is to the closest solution. For example, if it's five moves away from something that looks about 37 moves away from finishing, then it's about 42 moves away now.
The problem with this is that when you start it, it will have no idea how close anything is to the solution except for the solution, and there's no way it's getting to that by chance.
Essentially, you'd have to cheat and start by giving it almost solved Rubik's cubes, and slowly giving it more randomized ones. It won't learn on its own, but you can teach it pretty easily.
A less cheating-ish solution is to use some reasonable-seeming heuristic to guess how close you are to a solution. For example, you could just count the number of squares "in the right place" after a move sequence.
(First post, bear with me.. find the site very interesting :)
I do agree!
But actually I would model the problem with what is known in some circles as a closed-loop controller, and specifically with a POMDP. Then apply RealTime Dynamic Prog. by embedding an heuristic without having to visit all the states in order to compute the rough but optimal h*.
Another way could be done by means of a graphical model, and more specifically a DAG would be quite nicely suited to the problem. Apply a simulated annealing approach (Ising model!) and when you reach "thermal equilibrium" by having minimized some energy functional you get the solution. Obviously this approach would involve learning the parameters of the model, instead of modelling the problem as in my first proposed approach.
Quite geeky, excuse me!