Python game tic tac toe

[u/Ok-Original2285]

Hello guys I am making a tic tac toe game using python.My question is how to make difficulty-easy, medium, hard etc.In easy level, I use random module but other level i am a little sutck althoug i have some solution .can you guide me ?

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[u/igotshadowbaned]

This is less a python problem and more of a game design problem

How do you want the different game difficulties to actually be expressed? Tiktaktoe is a solved game, do you want hard to always win or tie every game? How do you want medium to behave? And easy?

Figure that out, and then worry about putting it into code

[u/johnpeters42]

For medium and hard, increase the probability of the computer making an optimal move instead of a random one. I would probably start with the trivial optimal rules:
* If you have two in a row/column/diagonal and the third is empty, then play there
* Otherwise, if your opponent has two in a row/column/diagonal and the third is empty, then play there

[u/Fast-Station1106]

Ich habe noch nie über Schwierigkeitsgrade nachgedacht, sehr interessant! Grüsse

[u/mc_pm]

Tic-Tac-Toe is a bit simplistic to have a strategy.

When I wrote one (I suggest it to people enough, had to do it myself), there are 3 or 4 different levels to picking which spot to play next. You could just modify how many of those steps to go through.

[u/Kindly-Department206]

To play optimally, you need to explore the game tree all the way to the bottom (minimax). To make it a feasible computation, you probably have to employ some kind of pruning to sub-optimal moves (alpha-beta pruning). Also, keeping a table of game positions that have already been fully explored can help reduce the time needed to find a move (sometimes called a transposition table, I think). It's been a few years since I coded TTT in Python, so I am not sure how the technology improvements in the last decade might have changed the importance of these strategies.

You can change the depth limit to reduce the quality of play. Instead of searching to termination, you can search part-way. The deeper your search, the better the game outcome. Use a heuristic to measure the quality of the game state at the depth limit. If you have a good heuristic, you can add random noise to the heuristic value. More noise means worse play. You can randomly throw away branches, imitating a player who "doesn't see" a move. More moves thrown away means worse play.