Estimating the strength of poker hands by integer linear programming techniques

We illustrate how Integer Linear Programming techniques can be applied to the popular game of poker Texas Hold'em in order to evaluate the strength of a hand. In particular, we give models aimed at (i) minimizing the number of features that a player should look at when estimating his winning probability (called his {em equity}); (ii) giving weights to such features so that the equity is approximated by the weighted sum of the selected features. We show that ten features or less are enough to estimate the equity of a hand with high precision.