  Approximating a Nash equilibrium is currently the best performing approach
for creating poker-playing programs. While for the simplest variants of the
game, it is possible to evaluate the quality of the approximation by computing
the value of the best response strategy, this is currently not computationally
feasible for larger variants of the game, such as heads-up no-limit Texas
hold'em. In this paper, we present a simple and computationally inexpensive
Local Best Response method for computing an approximate lower bound on the
value of the best response strategy. Using this method, we show that existing
poker-playing programs, based on solving abstract games, are remarkably poor
Nash equilibrium approximations.
