![]() That way our bot will always pick the best move given a particular game state. We’ll leverage minimax searching to simulate every possible move and counter move. Today we’re going to teach our bot how to play tic tac toe using a brute force solution, minimax searching. That’s changing a bit with the rise of deep learning. Our programs tell bots exactly what to do in each circumstance. ![]() Historically that’s done via a rules or brute force based approach. Humans have to program bots how to play games. On the other hand, how do bots play games? It’s harder for a bot to build an “intuition” about games. You begin to gather an intuition about the game. Over time, you begin to understand which strategies are better or worse. If I play there, and he plays there, then I could play there, so on and so on. Which deciding on a move, you would probably mentally play out how the game would progress. Tic tac toe might be a simple game, but it’s useful to teach strategies for how some computers approach playing games. Today I’m going to walk you through what is takes to write a tic tac toe bot. Games are fun! Programming computers to play games is also fun! I won’t discuss minimax in depth here, so please check out that article if you have questions about minimax. This article builds upon last week’s minimax searching article.
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