I would like to explain some first class game theory here.
You have 3 main euler powers in game theory :
1. Gaussian Support Vector Machines, which gives you a good AI.
2. Statisics, for interpolating probabilities and sampling as in data mining for e.g. a Chess program.
3. Boltzman : for gaining entropy with a random walk.
You can find these things in several languages on http://wikipedia.org
<-- in the search bar
I will explain further on how these can be used in game mechanics.
3. Boltzman just adds energy/entropy by keeping an ascent. If you play a jackpot game a few times you will have a jackpot outcome which is a gain in entropy due to a random walk.
2. If you study Monte Carlo sampling methods (e.g. a HMM, Hidden Markov Model) you will see that the integral or differentiation of this formula needs a probability distribution.
I will further comment on in this topic what you can do with these floating point unit interpolation methods.