You want to build your own Tic-Tac-Toe opponent? Then you need to read further! In the Tic-Tac-AI series, I will present a couple of Artificial Intelligence algorithms implemented as Tic-Tac-Toe opponent. In this first article, I will introduce a method called Forward Sampling which is capable of not losing any game of Tic-Tac-Toe!

# probability density function

## Win with gambling: MAP estimation on a Bernoulli distribution

In this article, we will try to win a (fictive) lottery called Win-Win. In fact, you will learn how to do a MAP (maximum a posteriori) estimation on a Bernoulli distribution. Don’t worry if you don’t know all these words, everything will be explained. If you already know some of the terms, then you can skip these parts. (more…)

## The Mathematics Behind: Rejection Sampling

Suppose that we have a probability density function (PDF) that is impossible to analyze analytically. How can we ever draw samples from this PDF? Luckily, there are many techniques out there and this time I will highlight rejection sampling. A simple to implement (but not always effective) sampling method.