Summary

In this chapter, we learned how to apply search techniques to play games.

First, we created a static approach that played the Tic-Tac-Toe game based on predefined rules without looking ahead. Then, we quantified these rules into a number we called heuristics. In the next topic, we learned how to use heuristics in the A* search algorithm to find an optimal solution to a problem.

Finally, we got to know the Minmax and the NegaMax algorithms so that the AI could win two-player games.

Now that you know the fundamentals of writing game AI, it is time to learn about a different field within artificial intelligence: machine learning. In the next chapter, you will learn about regression.