Finding the minimum approximate ratio for Nash equilibrium of bi-matrix games
has derived a series of studies, started with 3/4, followed by 1/2, 0.38 and
0.36, finally the best approximate ratio of 0.3393 by Tsaknakis and Spirakis
(TS algorithm for short). Efforts to improve the results remain not successful
in the past 14 years. This work makes the first progress to show that the bound
of 0.3393 is indeed tight for the TS algorithm. Next, we characterize all
possible tight game instances for the TS algorithm. It allows us to conduct
extensive experiments to study the nature of the TS algorithm and to compare it
with other algorithms. We find that this lower bound is not smoothed for the TS
algorithm in that any perturbation on the initial point may deviate away from
this tight bound approximate solution. Other approximate algorithms such as
Fictitious Play and Regret Matching also find better approximate solutions.
However, the new distributed algorithm for approximate Nash equilibrium by
Czumaj et al. performs consistently at the same bound of 0.3393. This proves
our lower bound instances generated against the TS algorithm can serve as a
benchmark in design and analysis of approximate Nash equilibrium algorithms