This document is devoted to artificial intelligence and optimization. This part will be devoted to having fun with high level ideas and to introduce the subject. Thereafter, Part II will be devoted to Monte-Carlo Tree Search, a recent great tool for sequential decision making; we will only briefly discuss other tools for sequential decision making; the complexity of sequential decision making will be reviewed. Then, part III will discuss optimization, with a particular focus on robust optimization and especially evolutionary optimization. Part IV will present some machine learning tools, useful in everyday life, such as supervised learning and active learning. A conclusion (part V) will come back to fun and to high level ideas.