mlatinjo wrote:

hi it is average over all run outs.

Do you really plan to implement it? Just imagine how many operations would you need to perform, in order to evaluate the whole game tree. How many possible boards you have, how many possible actions and opponent actions. The reason why gto is not solved in poker is because game tree is huge, so there are only approximations of game tree which yield solid results.

What are these approximations that they make, I'm just so confused right now. My method was going to be to just process a tree with capped actions and sizes for hand vs hand, monte-carlo the possible board run-outs, have a training period of 100,000 boards with uniform strategy/probabilities and then start using CFR algorithm on the regrets after this training period. And that should have given me some sort of result like 70% bet, 30% check this flop with this hand.

jackrabbit wrote:

Actually implementing something like this will require some extraordinary amount of cleverness if you want to arrive at anything useful. As mentioned, the game tree in poker can get huge, so some form of size-reduction (game abstraction, pruning, limited-lookahead) has to be implemented whenever you work with a real decision tree.

In reality, you should probably reconsider the way you implement this EV-estimation you're trying to do.

Yep I'm already beginning to reconsider it after reading your two replies. The only problem is I don't know what else to try really. Wouldn't an abstracted game just limit the number of boards we look at, how would it actually shrink the tree itself (depth-wise)? It would just reduce the number of trees (one per board?)?

My aim was just to have a simple solid approximation of the best strategy given a hand on a board vs a range.